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Package bigquery provides a client for the BigQuery service.
The following assumes a basic familiarity with BigQuery concepts. See https://cloud.google.com/bigquery/docs.
See https://godoc.org/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package.
Creating a Client
To start working with this package, create a client:
ctx := context.Background() client, err := bigquery.NewClient(ctx, projectID) if err != nil { // TODO: Handle error. }
Querying
To query existing tables, create a Query and call its Read method, which starts the query and waits for it to complete:
q := client.Query(` SELECT year, SUM(number) as num FROM bigquery-public-data.usa_names.usa_1910_2013 WHERE name = @name GROUP BY year ORDER BY year `) q.Parameters = []bigquery.QueryParameter{ {Name: "name", Value: "William"}, } it, err := q.Read(ctx) if err != nil { // TODO: Handle error. }
Then iterate through the resulting rows. You can store a row using anything that implements the ValueLoader interface, or with a slice or map of bigquery.Value. A slice is simplest:
for { var values []bigquery.Value err := it.Next(&values) if err == iterator.Done { break } if err != nil { // TODO: Handle error. } fmt.Println(values) }
You can also use a struct whose exported fields match the query:
type Count struct { Year int Num int } for { var c Count err := it.Next(&c) if err == iterator.Done { break } if err != nil { // TODO: Handle error. } fmt.Println(c) }
You can also start the query running and get the results later. Create the query as above, but call Run instead of Read. This returns a Job, which represents an asynchronous operation.
job, err := q.Run(ctx) if err != nil { // TODO: Handle error. }
Get the job's ID, a printable string. You can save this string to retrieve the results at a later time, even in another process.
jobID := job.ID() fmt.Printf("The job ID is %s\n", jobID)
To retrieve the job's results from the ID, first look up the Job:
job, err = client.JobFromID(ctx, jobID) if err != nil { // TODO: Handle error. }
Use the Job.Read method to obtain an iterator, and loop over the rows. Calling Query.Read is preferred for queries with a relatively small result set, as it will call BigQuery jobs.query API for a optimized query path. If the query doesn't meet that criteria, the method will just combine Query.Run and Job.Read.
it, err = job.Read(ctx) if err != nil { // TODO: Handle error. } // Proceed with iteration as above.
Datasets and Tables
You can refer to datasets in the client's project with the Dataset method, and in other projects with the DatasetInProject method:
myDataset := client.Dataset("my_dataset") yourDataset := client.DatasetInProject("your-project-id", "your_dataset")
These methods create references to datasets, not the datasets themselves. You can have a dataset reference even if the dataset doesn't exist yet. Use Dataset.Create to create a dataset from a reference:
if err := myDataset.Create(ctx, nil); err != nil { // TODO: Handle error. }
You can refer to tables with Dataset.Table. Like bigquery.Dataset, bigquery.Table is a reference to an object in BigQuery that may or may not exist.
table := myDataset.Table("my_table")
You can create, delete and update the metadata of tables with methods on Table. For instance, you could create a temporary table with:
err = myDataset.Table("temp").Create(ctx, &bigquery.TableMetadata{ ExpirationTime: time.Now().Add(1*time.Hour)}) if err != nil { // TODO: Handle error. }
We'll see how to create a table with a schema in the next section.
Schemas
There are two ways to construct schemas with this package. You can build a schema by hand, like so:
schema1 := bigquery.Schema{ {Name: "Name", Required: true, Type: bigquery.StringFieldType}, {Name: "Grades", Repeated: true, Type: bigquery.IntegerFieldType}, {Name: "Optional", Required: false, Type: bigquery.IntegerFieldType}, }
Or you can infer the schema from a struct:
type student struct { Name string Grades []int Optional bigquery.NullInt64 } schema2, err := bigquery.InferSchema(student{}) if err != nil { // TODO: Handle error. } // schema1 and schema2 are identical.
Struct inference supports tags like those of the encoding/json package, so you can change names, ignore fields, or mark a field as nullable (non-required). Fields declared as one of the Null types (NullInt64, NullFloat64, NullString, NullBool, NullTimestamp, NullDate, NullTime, NullDateTime, and NullGeography) are automatically inferred as nullable, so the "nullable" tag is only needed for []byte, *big.Rat and pointer-to-struct fields.
type student2 struct { Name string `bigquery:"full_name"` Grades []int Secret string `bigquery:"-"` Optional []byte `bigquery:",nullable"` } schema3, err := bigquery.InferSchema(student2{}) if err != nil { // TODO: Handle error. } // schema3 has required fields "full_name" and "Grade", and nullable BYTES field "Optional".
Having constructed a schema, you can create a table with it like so:
if err := table.Create(ctx, &bigquery.TableMetadata{Schema: schema1}); err != nil { // TODO: Handle error. }
Copying
You can copy one or more tables to another table. Begin by constructing a Copier describing the copy. Then set any desired copy options, and finally call Run to get a Job:
copier := myDataset.Table("dest").CopierFrom(myDataset.Table("src")) copier.WriteDisposition = bigquery.WriteTruncate job, err = copier.Run(ctx) if err != nil { // TODO: Handle error. }
You can chain the call to Run if you don't want to set options:
job, err = myDataset.Table("dest").CopierFrom(myDataset.Table("src")).Run(ctx) if err != nil { // TODO: Handle error. }
You can wait for your job to complete:
status, err := job.Wait(ctx) if err != nil { // TODO: Handle error. }
Job.Wait polls with exponential backoff. You can also poll yourself, if you wish:
for { status, err := job.Status(ctx) if err != nil { // TODO: Handle error. } if status.Done() { if status.Err() != nil { log.Fatalf("Job failed with error %v", status.Err()) } break } time.Sleep(pollInterval) }
Loading and Uploading
There are two ways to populate a table with this package: load the data from a Google Cloud Storage object, or upload rows directly from your program.
For loading, first create a GCSReference, configuring it if desired. Then make a Loader, optionally configure it as well, and call its Run method.
gcsRef := bigquery.NewGCSReference("gs://my-bucket/my-object") gcsRef.AllowJaggedRows = true loader := myDataset.Table("dest").LoaderFrom(gcsRef) loader.CreateDisposition = bigquery.CreateNever job, err = loader.Run(ctx) // Poll the job for completion if desired, as above.
To upload, first define a type that implements the ValueSaver interface, which has a single method named Save. Then create an Inserter, and call its Put method with a slice of values.
type Item struct { Name string Size float64 Count int } // Save implements the ValueSaver interface. func (i *Item) Save() (map[string]bigquery.Value, string, error) { return map[string]bigquery.Value{ "Name": i.Name, "Size": i.Size, "Count": i.Count, }, "", nil } u := table.Inserter() // Item implements the ValueSaver interface. items := []*Item{ {Name: "n1", Size: 32.6, Count: 7}, {Name: "n2", Size: 4, Count: 2}, {Name: "n3", Size: 101.5, Count: 1}, } if err := u.Put(ctx, items); err != nil { // TODO: Handle error. }
You can also upload a struct that doesn't implement ValueSaver. Use the StructSaver type to specify the schema and insert ID by hand:
type item struct { Name string Num int } // Assume schema holds the table's schema. savers := []*bigquery.StructSaver{ {Struct: score{Name: "n1", Num: 12}, Schema: schema, InsertID: "id1"}, {Struct: score{Name: "n2", Num: 31}, Schema: schema, InsertID: "id2"}, {Struct: score{Name: "n3", Num: 7}, Schema: schema, InsertID: "id3"}, } if err := u.Put(ctx, savers); err != nil { // TODO: Handle error. }
Lastly, but not least, you can just supply the struct or struct pointer directly and the schema will be inferred:
type Item2 struct { Name string Size float64 Count int } // Item2 doesn't implement ValueSaver interface, so schema will be inferred. items2 := []*Item2{ {Name: "n1", Size: 32.6, Count: 7}, {Name: "n2", Size: 4, Count: 2}, {Name: "n3", Size: 101.5, Count: 1}, } if err := u.Put(ctx, items2); err != nil { // TODO: Handle error. }
BigQuery allows for higher throughput when omitting insertion IDs. To enable this,
specify the sentinel NoDedupeID
value for the insertion ID when implementing a ValueSaver.
Extracting
If you've been following so far, extracting data from a BigQuery table into a Google Cloud Storage object will feel familiar. First create an Extractor, then optionally configure it, and lastly call its Run method.
extractor := table.ExtractorTo(gcsRef) extractor.DisableHeader = true job, err = extractor.Run(ctx) // Poll the job for completion if desired, as above.
Errors
Errors returned by this client are often of the type googleapi.Error: https://godoc.org/google.golang.org/api/googleapi#Error
These errors can be introspected for more information by using xerrors.As
with the richer *googleapi.Error type. For example:
var e *googleapi.Error if ok := xerrors.As(err, &e); ok { if e.Code == 409 { ... } }
In some cases, your client may received unstructured googleapi.Error error responses. In such cases, it is likely that you have exceeded BigQuery request limits, documented at: https://cloud.google.com/bigquery/quotas
Constants
LogicalStorageBillingModel, PhysicalStorageBillingModel
const (
// LogicalStorageBillingModel indicates billing for logical bytes.
LogicalStorageBillingModel = ""
// PhysicalStorageBillingModel indicates billing for physical bytes.
PhysicalStorageBillingModel = "PHYSICAL"
)
ScalarFunctionRoutine, ProcedureRoutine, TableValuedFunctionRoutine
const (
// ScalarFunctionRoutine scalar function routine type
ScalarFunctionRoutine = "SCALAR_FUNCTION"
// ProcedureRoutine procedure routine type
ProcedureRoutine = "PROCEDURE"
// TableValuedFunctionRoutine routine type for table valued functions
TableValuedFunctionRoutine = "TABLE_VALUED_FUNCTION"
)
NumericPrecisionDigits, NumericScaleDigits, BigNumericPrecisionDigits, BigNumericScaleDigits
const (
// NumericPrecisionDigits is the maximum number of digits in a NUMERIC value.
NumericPrecisionDigits = 38
// NumericScaleDigits is the maximum number of digits after the decimal point in a NUMERIC value.
NumericScaleDigits = 9
// BigNumericPrecisionDigits is the maximum number of full digits in a BIGNUMERIC value.
BigNumericPrecisionDigits = 76
// BigNumericScaleDigits is the maximum number of full digits in a BIGNUMERIC value.
BigNumericScaleDigits = 38
)
DetectProjectID
const DetectProjectID = "*detect-project-id*"
DetectProjectID is a sentinel value that instructs NewClient to detect the project ID. It is given in place of the projectID argument. NewClient will use the project ID from the given credentials or the default credentials (https://developers.google.com/accounts/docs/application-default-credentials) if no credentials were provided. When providing credentials, not all options will allow NewClient to extract the project ID. Specifically a JWT does not have the project ID encoded.
NoDedupeID
const NoDedupeID = "NoDedupeID"
NoDedupeID indicates a streaming insert row wants to opt out of best-effort deduplication. It is EXPERIMENTAL and subject to change or removal without notice.
Scope
const (
// Scope is the Oauth2 scope for the service.
// For relevant BigQuery scopes, see:
// https://developers.google.com/identity/protocols/googlescopes#bigqueryv2
Scope = "https://www.googleapis.com/auth/bigquery"
)
Variables
NeverExpire
NeverExpire is a sentinel value used to remove a table'e expiration time.
Functions
func BigNumericString
BigNumericString returns a string representing a *big.Rat in a format compatible with BigQuery SQL. It returns a floating point literal with 38 digits after the decimal point.
func CivilDateTimeString
CivilDateTimeString returns a string representing a civil.DateTime in a format compatible with BigQuery SQL. It separate the date and time with a space, and formats the time with CivilTimeString.
Use CivilDateTimeString when using civil.DateTime in DML, for example in INSERT statements.
func CivilTimeString
CivilTimeString returns a string representing a civil.Time in a format compatible with BigQuery SQL. It rounds the time to the nearest microsecond and returns a string with six digits of sub-second precision.
Use CivilTimeString when using civil.Time in DML, for example in INSERT statements.
func IntervalString
func IntervalString(iv *IntervalValue) string
IntervalString returns a string representing an *IntervalValue in a format compatible with BigQuery SQL. It returns an interval literal in canonical format.
func NewArrowIteratorReader
func NewArrowIteratorReader(it ArrowIterator) io.Reader
NewArrowIteratorReader allows to consume an ArrowIterator as an io.Reader. Experimental: this interface is experimental and may be modified or removed in future versions, regardless of any other documented package stability guarantees.
func NumericString
NumericString returns a string representing a *big.Rat in a format compatible with BigQuery SQL. It returns a floating-point literal with 9 digits after the decimal point.
func Seed
func Seed(s int64)
Seed seeds this package's random number generator, used for generating job and insert IDs. Use Seed to obtain repeatable, deterministic behavior from bigquery clients. Seed should be called before any clients are created.
AccessEntry
type AccessEntry struct {
Role AccessRole // The role of the entity
EntityType EntityType // The type of entity
Entity string // The entity (individual or group) granted access
View *Table // The view granted access (EntityType must be ViewEntity)
Routine *Routine // The routine granted access (only UDF currently supported)
Dataset *DatasetAccessEntry // The resources within a dataset granted access.
}
An AccessEntry describes the permissions that an entity has on a dataset.
AccessRole
type AccessRole string
AccessRole is the level of access to grant to a dataset.
OwnerRole, ReaderRole, WriterRole
const (
// OwnerRole is the OWNER AccessRole.
OwnerRole AccessRole = "OWNER"
// ReaderRole is the READER AccessRole.
ReaderRole AccessRole = "READER"
// WriterRole is the WRITER AccessRole.
WriterRole AccessRole = "WRITER"
)
ArrowIterator
type ArrowIterator interface {
Next() (*ArrowRecordBatch, error)
Schema() Schema
SerializedArrowSchema() []byte
}
ArrowIterator represents a way to iterate through a stream of arrow records. Experimental: this interface is experimental and may be modified or removed in future versions, regardless of any other documented package stability guarantees.
ArrowRecordBatch
type ArrowRecordBatch struct {
// Serialized Arrow Record Batch.
Data []byte
// Serialized Arrow Schema.
Schema []byte
// Source partition ID. In the Storage API world, it represents the ReadStream.
PartitionID string
// contains filtered or unexported fields
}
ArrowRecordBatch represents an Arrow RecordBatch with the source PartitionID
func (*ArrowRecordBatch) Read
func (r *ArrowRecordBatch) Read(p []byte) (int, error)
Read makes ArrowRecordBatch implements io.Reader
AvroOptions
type AvroOptions struct {
// UseAvroLogicalTypes indicates whether to interpret logical types as the
// corresponding BigQuery data type (for example, TIMESTAMP), instead of using
// the raw type (for example, INTEGER).
UseAvroLogicalTypes bool
}
AvroOptions are additional options for Avro external data data sources.
BIEngineReason
type BIEngineReason struct {
// High-Level BI engine reason for partial or disabled acceleration.
Code string
// Human-readable reason for partial or disabled acceleration.
Message string
}
BIEngineReason contains more detailed information about why a query wasn't fully accelerated.
BIEngineStatistics
type BIEngineStatistics struct {
// Specifies which mode of BI Engine acceleration was performed.
BIEngineMode string
// In case of DISABLED or PARTIAL BIEngineMode, these
// contain the explanatory reasons as to why BI Engine could not
// accelerate. In case the full query was accelerated, this field is not
// populated.
BIEngineReasons []*BIEngineReason
}
BIEngineStatistics contains query statistics specific to the use of BI Engine.
BigtableColumn
type BigtableColumn struct {
// Qualifier of the column. Columns in the parent column family that have this
// exact qualifier are exposed as . field. The column field name is the
// same as the column qualifier.
Qualifier string
// If the qualifier is not a valid BigQuery field identifier i.e. does not match
// [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field
// name and is used as field name in queries.
FieldName string
// If true, only the latest version of values are exposed for this column.
// See BigtableColumnFamily.OnlyReadLatest.
OnlyReadLatest bool
// The encoding of the values when the type is not STRING.
// See BigtableColumnFamily.Encoding
Encoding string
// The type to convert the value in cells of this column.
// See BigtableColumnFamily.Type
Type string
}
BigtableColumn describes how BigQuery should access a Bigtable column.
BigtableColumnFamily
type BigtableColumnFamily struct {
// Identifier of the column family.
FamilyID string
// Lists of columns that should be exposed as individual fields as opposed to a
// list of (column name, value) pairs. All columns whose qualifier matches a
// qualifier in this list can be accessed as .. Other columns can be accessed as
// a list through .Column field.
Columns []*BigtableColumn
// The encoding of the values when the type is not STRING. Acceptable encoding values are:
// - TEXT - indicates values are alphanumeric text strings.
// - BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions.
// This can be overridden for a specific column by listing that column in 'columns' and
// specifying an encoding for it.
Encoding string
// If true, only the latest version of values are exposed for all columns in this
// column family. This can be overridden for a specific column by listing that
// column in 'columns' and specifying a different setting for that column.
OnlyReadLatest bool
// The type to convert the value in cells of this
// column family. The values are expected to be encoded using HBase
// Bytes.toBytes function when using the BINARY encoding value.
// Following BigQuery types are allowed (case-sensitive):
// BYTES STRING INTEGER FLOAT BOOLEAN.
// The default type is BYTES. This can be overridden for a specific column by
// listing that column in 'columns' and specifying a type for it.
Type string
}
BigtableColumnFamily describes how BigQuery should access a Bigtable column family.
BigtableOptions
type BigtableOptions struct {
// A list of column families to expose in the table schema along with their
// types. If omitted, all column families are present in the table schema and
// their values are read as BYTES.
ColumnFamilies []*BigtableColumnFamily
// If true, then the column families that are not specified in columnFamilies
// list are not exposed in the table schema. Otherwise, they are read with BYTES
// type values. The default is false.
IgnoreUnspecifiedColumnFamilies bool
// If true, then the rowkey column families will be read and converted to string.
// Otherwise they are read with BYTES type values and users need to manually cast
// them with CAST if necessary. The default is false.
ReadRowkeyAsString bool
}
BigtableOptions are additional options for Bigtable external data sources.
CSVOptions
type CSVOptions struct {
// AllowJaggedRows causes missing trailing optional columns to be tolerated
// when reading CSV data. Missing values are treated as nulls.
AllowJaggedRows bool
// AllowQuotedNewlines sets whether quoted data sections containing
// newlines are allowed when reading CSV data.
AllowQuotedNewlines bool
// Encoding is the character encoding of data to be read.
Encoding Encoding
// FieldDelimiter is the separator for fields in a CSV file, used when
// reading or exporting data. The default is ",".
FieldDelimiter string
// Quote is the value used to quote data sections in a CSV file. The
// default quotation character is the double quote ("), which is used if
// both Quote and ForceZeroQuote are unset.
// To specify that no character should be interpreted as a quotation
// character, set ForceZeroQuote to true.
// Only used when reading data.
Quote string
ForceZeroQuote bool
// The number of rows at the top of a CSV file that BigQuery will skip when
// reading data.
SkipLeadingRows int64
// An optional custom string that will represent a NULL
// value in CSV import data.
NullMarker string
// Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table,
// from '\\x00' to '\\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
PreserveASCIIControlCharacters bool
}
CSVOptions are additional options for CSV external data sources.
Client
type Client struct {
// Location, if set, will be used as the default location for all subsequent
// dataset creation and job operations. A location specified directly in one of
// those operations will override this value.
Location string
// contains filtered or unexported fields
}
Client may be used to perform BigQuery operations.
func NewClient
NewClient constructs a new Client which can perform BigQuery operations. Operations performed via the client are billed to the specified GCP project.
If the project ID is set to DetectProjectID, NewClient will attempt to detect the project ID from credentials.
This client supports enabling query-related preview features via environmental variables. By setting the environment variable QUERY_PREVIEW_ENABLED to the string "TRUE", the client will enable preview features, though behavior may still be controlled via the bigquery service as well. Currently, the feature(s) in scope include: short mode queries (query execution without corresponding job metadata).
Example
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
_ = client // TODO: Use client.
}
func (*Client) Close
Close closes any resources held by the client. Close should be called when the client is no longer needed. It need not be called at program exit.
func (*Client) Dataset
Dataset creates a handle to a BigQuery dataset in the client's project.
Example
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ds := client.Dataset("my_dataset")
fmt.Println(ds)
}
func (*Client) DatasetInProject
DatasetInProject creates a handle to a BigQuery dataset in the specified project.
Example
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ds := client.DatasetInProject("their-project-id", "their-dataset")
fmt.Println(ds)
}
func (*Client) Datasets
func (c *Client) Datasets(ctx context.Context) *DatasetIterator
Datasets returns an iterator over the datasets in a project. The Client's project is used by default, but that can be changed by setting ProjectID on the returned iterator before calling Next.
Example
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
it := client.Datasets(ctx)
_ = it // TODO: iterate using Next or iterator.Pager.
}
func (*Client) DatasetsInProject (deprecated)
func (c *Client) DatasetsInProject(ctx context.Context, projectID string) *DatasetIterator
DatasetsInProject returns an iterator over the datasets in the provided project.
Deprecated: call Client.Datasets, then set ProjectID on the returned iterator.
Example
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
it := client.DatasetsInProject(ctx, "their-project-id")
_ = it // TODO: iterate using Next or iterator.Pager.
}
func (*Client) EnableStorageReadClient
EnableStorageReadClient sets up Storage API connection to be used when fetching large datasets from tables, jobs or queries. Currently out of pagination methods like PageInfo().Token and RowIterator.StartIndex are not supported when the Storage API is enabled. Calling this method twice will return an error.
func (*Client) JobFromID
JobFromID creates a Job which refers to an existing BigQuery job. The job need not have been created by this package. For example, the job may have been created in the BigQuery console.
For jobs whose location is other than "US" or "EU", set Client.Location or use JobFromIDLocation.
Example
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
func getJobID() string { return "" }
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
jobID := getJobID() // Get a job ID using Job.ID, the console or elsewhere.
job, err := client.JobFromID(ctx, jobID)
if err != nil {
// TODO: Handle error.
}
fmt.Println(job.LastStatus()) // Display the job's status.
}
func (*Client) JobFromIDLocation
JobFromIDLocation creates a Job which refers to an existing BigQuery job. The job need not have been created by this package (for example, it may have been created in the BigQuery console), but it must exist in the specified location.
func (*Client) JobFromProject
func (c *Client) JobFromProject(ctx context.Context, projectID, jobID, location string) (j *Job, err error)
JobFromProject creates a Job which refers to an existing BigQuery job. The job need not have been created by this package, nor does it need to reside within the same project or location as the instantiated client.
func (*Client) Jobs
func (c *Client) Jobs(ctx context.Context) *JobIterator
Jobs lists jobs within a project.
Example
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
it := client.Jobs(ctx)
it.State = bigquery.Running // list only running jobs.
_ = it // TODO: iterate using Next or iterator.Pager.
}
func (*Client) Project
Project returns the project ID or number for this instance of the client, which may have either been explicitly specified or autodetected.
func (*Client) Query
Query creates a query with string q. The returned Query may optionally be further configured before its Run method is called.
Examples
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
q := client.Query("select name, num from t1")
q.DefaultProjectID = "project-id"
// TODO: set other options on the Query.
// TODO: Call Query.Run or Query.Read.
}
encryptionKey
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
q := client.Query("select name, num from t1")
// TODO: Replace this key with a key you have created in Cloud KMS.
keyName := "projects/P/locations/L/keyRings/R/cryptoKeys/K"
q.DestinationEncryptionConfig = &bigquery.EncryptionConfig{KMSKeyName: keyName}
// TODO: set other options on the Query.
// TODO: Call Query.Run or Query.Read.
}
parameters
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
q := client.Query("select num from t1 where name = @user")
q.Parameters = []bigquery.QueryParameter{
{Name: "user", Value: "Elizabeth"},
}
// TODO: set other options on the Query.
// TODO: Call Query.Run or Query.Read.
}
CloneDefinition
type CloneDefinition struct {
// BaseTableReference describes the ID of the table that this clone
// came from.
BaseTableReference *Table
// CloneTime indicates when the base table was cloned.
CloneTime time.Time
}
CloneDefinition provides metadata related to the origin of a clone.
Clustering
type Clustering struct {
Fields []string
}
Clustering governs the organization of data within a managed table. For more information, see https://cloud.google.com/bigquery/docs/clustered-tables
ColumnNameCharacterMap
type ColumnNameCharacterMap string
ColumnNameCharacterMap is used to specific column naming behavior for load jobs.
UnspecifiedColumnNameCharacterMap, StrictColumnNameCharacterMap, V1ColumnNameCharacterMap, V2ColumnNameCharacterMap
var (
// UnspecifiedColumnNameCharacterMap is the unspecified default value.
UnspecifiedColumnNameCharacterMap ColumnNameCharacterMap = "COLUMN_NAME_CHARACTER_MAP_UNSPECIFIED"
// StrictColumnNameCharacterMap indicates support for flexible column names.
// Invalid column names will be rejected.
StrictColumnNameCharacterMap ColumnNameCharacterMap = "STRICT"
// V1ColumnNameCharacterMap indicates support for alphanumeric + underscore characters and names must start with a letter or underscore.
// Invalid column names will be normalized.
V1ColumnNameCharacterMap ColumnNameCharacterMap = "V1"
// V2ColumnNameCharacterMap indicates support for flexible column names.
// Invalid column names will be normalized.
V2ColumnNameCharacterMap ColumnNameCharacterMap = "V2"
)
ColumnReference
type ColumnReference struct {
// ReferencingColumn is the column in the current table that composes the foreign key.
ReferencingColumn string
// ReferencedColumn is the column in the primary key of the foreign table that
// is referenced by the ReferencingColumn.
ReferencedColumn string
}
ColumnReference represents the pair of the foreign key column and primary key column.
Compression
type Compression string
Compression is the type of compression to apply when writing data to Google Cloud Storage.
None, Gzip, Deflate, Snappy
const (
// None specifies no compression.
None Compression = "NONE"
// Gzip specifies gzip compression.
Gzip Compression = "GZIP"
// Deflate specifies DEFLATE compression for Avro files.
Deflate Compression = "DEFLATE"
// Snappy specifies SNAPPY compression for Avro files.
Snappy Compression = "SNAPPY"
)
ConnectionProperty
type ConnectionProperty struct {
// Name of the connection property to set.
Key string
// Value of the connection property.
Value string
}
ConnectionProperty represents a single key and value pair that can be sent alongside a query request or load job.
Copier
type Copier struct {
JobIDConfig
CopyConfig
// contains filtered or unexported fields
}
A Copier copies data into a BigQuery table from one or more BigQuery tables.
func (*Copier) Run
Run initiates a copy job.
CopyConfig
type CopyConfig struct {
// Srcs are the tables from which data will be copied.
Srcs []*Table
// Dst is the table into which the data will be copied.
Dst *Table
// CreateDisposition specifies the circumstances under which the destination table will be created.
// The default is CreateIfNeeded.
CreateDisposition TableCreateDisposition
// WriteDisposition specifies how existing data in the destination table is treated.
// The default is WriteEmpty.
WriteDisposition TableWriteDisposition
// The labels associated with this job.
Labels map[string]string
// Custom encryption configuration (e.g., Cloud KMS keys).
DestinationEncryptionConfig *EncryptionConfig
// One of the supported operation types when executing a Table Copy jobs. By default this
// copies tables, but can also be set to perform snapshot or restore operations.
OperationType TableCopyOperationType
// Sets a best-effort deadline on a specific job. If job execution exceeds this
// timeout, BigQuery may attempt to cancel this work automatically.
//
// This deadline cannot be adjusted or removed once the job is created. Consider
// using Job.Cancel in situations where you need more dynamic behavior.
//
// Experimental: this option is experimental and may be modified or removed in future versions,
// regardless of any other documented package stability guarantees.
JobTimeout time.Duration
}
CopyConfig holds the configuration for a copy job.
DMLStatistics
type DMLStatistics struct {
// Rows added by the statement.
InsertedRowCount int64
// Rows removed by the statement.
DeletedRowCount int64
// Rows changed by the statement.
UpdatedRowCount int64
}
DMLStatistics contains counts of row mutations triggered by a DML query statement.
DataFormat
type DataFormat string
DataFormat describes the format of BigQuery table data.
CSV, Avro, JSON, DatastoreBackup, GoogleSheets, Bigtable, Parquet, ORC, TFSavedModel, XGBoostBooster, Iceberg
const (
CSV DataFormat = "CSV"
Avro DataFormat = "AVRO"
JSON DataFormat = "NEWLINE_DELIMITED_JSON"
DatastoreBackup DataFormat = "DATASTORE_BACKUP"
GoogleSheets DataFormat = "GOOGLE_SHEETS"
Bigtable DataFormat = "BIGTABLE"
Parquet DataFormat = "PARQUET"
ORC DataFormat = "ORC"
// For BQ ML Models, TensorFlow Saved Model format.
TFSavedModel DataFormat = "ML_TF_SAVED_MODEL"
// For BQ ML Models, xgBoost Booster format.
XGBoostBooster DataFormat = "ML_XGBOOST_BOOSTER"
Iceberg DataFormat = "ICEBERG"
)
Constants describing the format of BigQuery table data.
Dataset
Dataset is a reference to a BigQuery dataset.
func (*Dataset) Create
func (d *Dataset) Create(ctx context.Context, md *DatasetMetadata) (err error)
Create creates a dataset in the BigQuery service. An error will be returned if the dataset already exists. Pass in a DatasetMetadata value to configure the dataset.
Example
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ds := client.Dataset("my_dataset")
if err := ds.Create(ctx, &bigquery.DatasetMetadata{Location: "EU"}); err != nil {
// TODO: Handle error.
}
}
func (*Dataset) Delete
Delete deletes the dataset. Delete will fail if the dataset is not empty.
Example
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
if err := client.Dataset("my_dataset").Delete(ctx); err != nil {
// TODO: Handle error.
}
}
func (*Dataset) DeleteWithContents
DeleteWithContents deletes the dataset, as well as contained resources.
func (*Dataset) Identifier
func (d *Dataset) Identifier(f IdentifierFormat) (string, error)
Identifier returns the ID of the dataset in the requested format.
For Standard SQL format, the identifier will be quoted if the ProjectID contains dash (-) characters.
func (*Dataset) Metadata
func (d *Dataset) Metadata(ctx context.Context) (md *DatasetMetadata, err error)
Metadata fetches the metadata for the dataset.
Example
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
md, err := client.Dataset("my_dataset").Metadata(ctx)
if err != nil {
// TODO: Handle error.
}
fmt.Println(md)
}
func (*Dataset) Model
Model creates a handle to a BigQuery model in the dataset. To determine if a model exists, call Model.Metadata. If the model does not already exist, you can create it via execution of a CREATE MODEL query.
func (*Dataset) Models
func (d *Dataset) Models(ctx context.Context) *ModelIterator
Models returns an iterator over the models in the Dataset.
func (*Dataset) Routine
Routine creates a handle to a BigQuery routine in the dataset. To determine if a routine exists, call Routine.Metadata.
func (*Dataset) Routines
func (d *Dataset) Routines(ctx context.Context) *RoutineIterator
Routines returns an iterator over the routines in the Dataset.
func (*Dataset) Table
Table creates a handle to a BigQuery table in the dataset. To determine if a table exists, call Table.Metadata. If the table does not already exist, use Table.Create to create it.
Example
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
// Table creates a reference to the table. It does not create the actual
// table in BigQuery; to do so, use Table.Create.
t := client.Dataset("my_dataset").Table("my_table")
fmt.Println(t)
}
func (*Dataset) Tables
func (d *Dataset) Tables(ctx context.Context) *TableIterator
Tables returns an iterator over the tables in the Dataset.
Example
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
it := client.Dataset("my_dataset").Tables(ctx)
_ = it // TODO: iterate using Next or iterator.Pager.
}
func (*Dataset) Update
func (d *Dataset) Update(ctx context.Context, dm DatasetMetadataToUpdate, etag string) (md *DatasetMetadata, err error)
Update modifies specific Dataset metadata fields. To perform a read-modify-write that protects against intervening reads, set the etag argument to the DatasetMetadata.ETag field from the read. Pass the empty string for etag for a "blind write" that will always succeed.
Examples
blindWrite
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
md, err := client.Dataset("my_dataset").Update(ctx, bigquery.DatasetMetadataToUpdate{Name: "blind"}, "")
if err != nil {
// TODO: Handle error.
}
fmt.Println(md)
}
readModifyWrite
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ds := client.Dataset("my_dataset")
md, err := ds.Metadata(ctx)
if err != nil {
// TODO: Handle error.
}
md2, err := ds.Update(ctx,
bigquery.DatasetMetadataToUpdate{Name: "new " + md.Name},
md.ETag)
if err != nil {
// TODO: Handle error.
}
fmt.Println(md2)
}
DatasetAccessEntry
type DatasetAccessEntry struct {
// The dataset to which this entry applies.
Dataset *Dataset
// The list of target types within the dataset
// to which this entry applies.
//
// Current supported values:
//
// VIEWS - This entry applies to views in the dataset.
TargetTypes []string
}
DatasetAccessEntry is an access entry that refers to resources within another dataset.
DatasetIterator
type DatasetIterator struct {
// ListHidden causes hidden datasets to be listed when set to true.
// Set before the first call to Next.
ListHidden bool
// Filter restricts the datasets returned by label. The filter syntax is described in
// https://cloud.google.com/bigquery/docs/labeling-datasets#filtering_datasets_using_labels
// Set before the first call to Next.
Filter string
// The project ID of the listed datasets.
// Set before the first call to Next.
ProjectID string
// contains filtered or unexported fields
}
DatasetIterator iterates over the datasets in a project.
func (*DatasetIterator) Next
func (it *DatasetIterator) Next() (*Dataset, error)
Next returns the next Dataset. Its second return value is iterator.Done if there are no more results. Once Next returns Done, all subsequent calls will return Done.
Example
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
"google.golang.org/api/iterator"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
it := client.Datasets(ctx)
for {
ds, err := it.Next()
if err == iterator.Done {
break
}
if err != nil {
// TODO: Handle error.
}
fmt.Println(ds)
}
}
func (*DatasetIterator) PageInfo
func (it *DatasetIterator) PageInfo() *iterator.PageInfo
PageInfo supports pagination. See the google.golang.org/api/iterator package for details.
DatasetMetadata
type DatasetMetadata struct {
// These fields can be set when creating a dataset.
Name string // The user-friendly name for this dataset.
Description string // The user-friendly description of this dataset.
Location string // The geo location of the dataset.
DefaultTableExpiration time.Duration // The default expiration time for new tables.
Labels map[string]string // User-provided labels.
Access []*AccessEntry // Access permissions.
DefaultEncryptionConfig *EncryptionConfig
// DefaultPartitionExpiration is the default expiration time for
// all newly created partitioned tables in the dataset.
DefaultPartitionExpiration time.Duration
// Defines the default collation specification of future tables
// created in the dataset. If a table is created in this dataset without
// table-level default collation, then the table inherits the dataset default
// collation, which is applied to the string fields that do not have explicit
// collation specified. A change to this field affects only tables created
// afterwards, and does not alter the existing tables.
// More information: https://cloud.google.com/bigquery/docs/reference/standard-sql/collation-concepts
DefaultCollation string
// For externally defined datasets, contains information about the configuration.
ExternalDatasetReference *ExternalDatasetReference
// MaxTimeTravel represents the number of hours for the max time travel for all tables
// in the dataset. Durations are rounded towards zero for the nearest hourly value.
MaxTimeTravel time.Duration
// Storage billing model to be used for all tables in the dataset.
// Can be set to PHYSICAL. Default is LOGICAL.
// Once you create a dataset with storage billing model set to physical bytes, you can't change it back to using logical bytes again.
// More details: https://cloud.google.com/bigquery/docs/datasets-intro#dataset_storage_billing_models
StorageBillingModel string
// These fields are read-only.
CreationTime time.Time
LastModifiedTime time.Time // When the dataset or any of its tables were modified.
FullID string // The full dataset ID in the form projectID:datasetID.
// The tags associated with this dataset. Tag keys are
// globally unique, and managed via the resource manager API.
// More information: https://cloud.google.com/resource-manager/docs/tags/tags-overview
Tags []*DatasetTag
// ETag is the ETag obtained when reading metadata. Pass it to Dataset.Update to
// ensure that the metadata hasn't changed since it was read.
ETag string
}
DatasetMetadata contains information about a BigQuery dataset.
DatasetMetadataToUpdate
type DatasetMetadataToUpdate struct {
Description optional.String // The user-friendly description of this table.
Name optional.String // The user-friendly name for this dataset.
// DefaultTableExpiration is the default expiration time for new tables.
// If set to time.Duration(0), new tables never expire.
DefaultTableExpiration optional.Duration
// DefaultTableExpiration is the default expiration time for
// all newly created partitioned tables.
// If set to time.Duration(0), new table partitions never expire.
DefaultPartitionExpiration optional.Duration
// DefaultEncryptionConfig defines CMEK settings for new resources created
// in the dataset.
DefaultEncryptionConfig *EncryptionConfig
// Defines the default collation specification of future tables
// created in the dataset.
DefaultCollation optional.String
// For externally defined datasets, contains information about the configuration.
ExternalDatasetReference *ExternalDatasetReference
// MaxTimeTravel represents the number of hours for the max time travel for all tables
// in the dataset. Durations are rounded towards zero for the nearest hourly value.
MaxTimeTravel optional.Duration
// Storage billing model to be used for all tables in the dataset.
// Can be set to PHYSICAL. Default is LOGICAL.
// Once you change a dataset's storage billing model to use physical bytes, you can't change it back to using logical bytes again.
// More details: https://cloud.google.com/bigquery/docs/datasets-intro#dataset_storage_billing_models
StorageBillingModel optional.String
// The entire access list. It is not possible to replace individual entries.
Access []*AccessEntry
// contains filtered or unexported fields
}
DatasetMetadataToUpdate is used when updating a dataset's metadata. Only non-nil fields will be updated.
func (*DatasetMetadataToUpdate) DeleteLabel
func (u *DatasetMetadataToUpdate) DeleteLabel(name string)
DeleteLabel causes a label to be deleted on a call to Update.
func (*DatasetMetadataToUpdate) SetLabel
func (u *DatasetMetadataToUpdate) SetLabel(name, value string)
SetLabel causes a label to be added or modified on a call to Update.
DatasetTag
type DatasetTag struct {
// TagKey is the namespaced friendly name of the tag key, e.g.
// "12345/environment" where 12345 is org id.
TagKey string
// TagValue is the friendly short name of the tag value, e.g.
// "production".
TagValue string
}
DatasetTag is a representation of a single tag key/value.
DecimalTargetType
type DecimalTargetType string
DecimalTargetType is used to express preference ordering for converting values from external formats.
NumericTargetType, BigNumericTargetType, StringTargetType
var (
// NumericTargetType indicates the preferred type is NUMERIC when supported.
NumericTargetType DecimalTargetType = "NUMERIC"
// BigNumericTargetType indicates the preferred type is BIGNUMERIC when supported.
BigNumericTargetType DecimalTargetType = "BIGNUMERIC"
// StringTargetType indicates the preferred type is STRING when supported.
StringTargetType DecimalTargetType = "STRING"
)
Encoding
type Encoding string
Encoding specifies the character encoding of data to be loaded into BigQuery. See https://cloud.google.com/bigquery/docs/reference/v2/jobs#configuration.load.encoding for more details about how this is used.
UTF_8, ISO_8859_1
const (
// UTF_8 specifies the UTF-8 encoding type.
UTF_8 Encoding = "UTF-8"
// ISO_8859_1 specifies the ISO-8859-1 encoding type.
ISO_8859_1 Encoding = "ISO-8859-1"
)
EncryptionConfig
type EncryptionConfig struct {
// Describes the Cloud KMS encryption key that will be used to protect
// destination BigQuery table. The BigQuery Service Account associated with your
// project requires access to this encryption key.
KMSKeyName string
}
EncryptionConfig configures customer-managed encryption on tables and ML models.
EntityType
type EntityType int
EntityType is the type of entity in an AccessEntry.
DomainEntity, GroupEmailEntity, UserEmailEntity, SpecialGroupEntity, ViewEntity, IAMMemberEntity, RoutineEntity, DatasetEntity
const (
// DomainEntity is a domain (e.g. "example.com").
DomainEntity EntityType = iota + 1
// GroupEmailEntity is an email address of a Google Group.
GroupEmailEntity
// UserEmailEntity is an email address of an individual user.
UserEmailEntity
// SpecialGroupEntity is a special group: one of projectOwners, projectReaders, projectWriters or
// allAuthenticatedUsers.
SpecialGroupEntity
// ViewEntity is a BigQuery logical view.
ViewEntity
// IAMMemberEntity represents entities present in IAM but not represented using
// the other entity types.
IAMMemberEntity
// RoutineEntity is a BigQuery routine, referencing a User Defined Function (UDF).
RoutineEntity
// DatasetEntity is BigQuery dataset, present in the access list.
DatasetEntity
)
Error
type Error struct {
// Mirrors bq.ErrorProto, but drops DebugInfo
Location, Message, Reason string
}
An Error contains detailed information about a failed bigquery operation. Detailed description of possible Reasons can be found here: https://cloud.google.com/bigquery/troubleshooting-errors.
func (Error) Error
ExplainQueryStage
type ExplainQueryStage struct {
// CompletedParallelInputs: Number of parallel input segments completed.
CompletedParallelInputs int64
// ComputeAvg: Duration the average shard spent on CPU-bound tasks.
ComputeAvg time.Duration
// ComputeMax: Duration the slowest shard spent on CPU-bound tasks.
ComputeMax time.Duration
// Relative amount of the total time the average shard spent on CPU-bound tasks.
ComputeRatioAvg float64
// Relative amount of the total time the slowest shard spent on CPU-bound tasks.
ComputeRatioMax float64
// EndTime: Stage end time.
EndTime time.Time
// Unique ID for stage within plan.
ID int64
// InputStages: IDs for stages that are inputs to this stage.
InputStages []int64
// Human-readable name for stage.
Name string
// ParallelInputs: Number of parallel input segments to be processed.
ParallelInputs int64
// ReadAvg: Duration the average shard spent reading input.
ReadAvg time.Duration
// ReadMax: Duration the slowest shard spent reading input.
ReadMax time.Duration
// Relative amount of the total time the average shard spent reading input.
ReadRatioAvg float64
// Relative amount of the total time the slowest shard spent reading input.
ReadRatioMax float64
// Number of records read into the stage.
RecordsRead int64
// Number of records written by the stage.
RecordsWritten int64
// ShuffleOutputBytes: Total number of bytes written to shuffle.
ShuffleOutputBytes int64
// ShuffleOutputBytesSpilled: Total number of bytes written to shuffle
// and spilled to disk.
ShuffleOutputBytesSpilled int64
// StartTime: Stage start time.
StartTime time.Time
// Current status for the stage.
Status string
// List of operations within the stage in dependency order (approximately
// chronological).
Steps []*ExplainQueryStep
// WaitAvg: Duration the average shard spent waiting to be scheduled.
WaitAvg time.Duration
// WaitMax: Duration the slowest shard spent waiting to be scheduled.
WaitMax time.Duration
// Relative amount of the total time the average shard spent waiting to be scheduled.
WaitRatioAvg float64
// Relative amount of the total time the slowest shard spent waiting to be scheduled.
WaitRatioMax float64
// WriteAvg: Duration the average shard spent on writing output.
WriteAvg time.Duration
// WriteMax: Duration the slowest shard spent on writing output.
WriteMax time.Duration
// Relative amount of the total time the average shard spent on writing output.
WriteRatioAvg float64
// Relative amount of the total time the slowest shard spent on writing output.
WriteRatioMax float64
}
ExplainQueryStage describes one stage of a query.
ExplainQueryStep
type ExplainQueryStep struct {
// Machine-readable operation type.
Kind string
// Human-readable stage descriptions.
Substeps []string
}
ExplainQueryStep describes one step of a query stage.
ExportDataStatistics
type ExportDataStatistics struct {
// Number of destination files generated.
FileCount int64
// Number of destination rows generated.
RowCount int64
}
ExportDataStatistics represents statistics for a EXPORT DATA statement as part of Query Job.
ExternalData
type ExternalData interface {
// contains filtered or unexported methods
}
ExternalData is a table which is stored outside of BigQuery. It is implemented by *ExternalDataConfig. GCSReference also implements it, for backwards compatibility.
ExternalDataConfig
type ExternalDataConfig struct {
// The format of the data. Required.
SourceFormat DataFormat
// The fully-qualified URIs that point to your
// data in Google Cloud. Required.
//
// For Google Cloud Storage URIs, each URI can contain one '*' wildcard character
// and it must come after the 'bucket' name. Size limits related to load jobs
// apply to external data sources.
//
// For Google Cloud Bigtable URIs, exactly one URI can be specified and it has be
// a fully specified and valid HTTPS URL for a Google Cloud Bigtable table.
//
// For Google Cloud Datastore backups, exactly one URI can be specified. Also,
// the '*' wildcard character is not allowed.
SourceURIs []string
// The schema of the data. Required for CSV and JSON; disallowed for the
// other formats.
Schema Schema
// Try to detect schema and format options automatically.
// Any option specified explicitly will be honored.
AutoDetect bool
// The compression type of the data.
Compression Compression
// IgnoreUnknownValues causes values not matching the schema to be
// tolerated. Unknown values are ignored. For CSV this ignores extra values
// at the end of a line. For JSON this ignores named values that do not
// match any column name. If this field is not set, records containing
// unknown values are treated as bad records. The MaxBadRecords field can
// be used to customize how bad records are handled.
IgnoreUnknownValues bool
// MaxBadRecords is the maximum number of bad records that will be ignored
// when reading data.
MaxBadRecords int64
// Additional options for CSV, GoogleSheets, Bigtable, and Parquet formats.
Options ExternalDataConfigOptions
// HivePartitioningOptions allows use of Hive partitioning based on the
// layout of objects in Google Cloud Storage.
HivePartitioningOptions *HivePartitioningOptions
// DecimalTargetTypes allows selection of how decimal values are converted when
// processed in bigquery, subject to the value type having sufficient precision/scale
// to support the values. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is
// selected if is present in the list and if supports the necessary precision and scale.
//
// StringTargetType supports all precision and scale values.
DecimalTargetTypes []DecimalTargetType
// ConnectionID associates an external data configuration with a connection ID.
// Connections are managed through the BigQuery Connection API:
// https://pkg.go.dev/cloud.google.com/go/bigquery/connection/apiv1
ConnectionID string
// When creating an external table, the user can provide a reference file with the table schema.
// This is enabled for the following formats: AVRO, PARQUET, ORC.
ReferenceFileSchemaURI string
}
ExternalDataConfig describes data external to BigQuery that can be used in queries and to create external tables.
ExternalDataConfigOptions
type ExternalDataConfigOptions interface {
// contains filtered or unexported methods
}
ExternalDataConfigOptions are additional options for external data configurations. This interface is implemented by CSVOptions, GoogleSheetsOptions and BigtableOptions.
ExternalDatasetReference
type ExternalDatasetReference struct {
//The connection id that is used to access the external_source.
// Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
Connection string
// External source that backs this dataset.
ExternalSource string
}
ExternalDatasetReference provides information about external dataset metadata.
ExtractConfig
type ExtractConfig struct {
// Src is the table from which data will be extracted.
// Only one of Src or SrcModel should be specified.
Src *Table
// SrcModel is the ML model from which the data will be extracted.
// Only one of Src or SrcModel should be specified.
SrcModel *Model
// Dst is the destination into which the data will be extracted.
Dst *GCSReference
// DisableHeader disables the printing of a header row in exported data.
DisableHeader bool
// The labels associated with this job.
Labels map[string]string
// For Avro-based extracts, controls whether logical type annotations are generated.
//
// Example: With this enabled, writing a BigQuery TIMESTAMP column will result in
// an integer column annotated with the appropriate timestamp-micros/millis annotation
// in the resulting Avro files.
UseAvroLogicalTypes bool
// Sets a best-effort deadline on a specific job. If job execution exceeds this
// timeout, BigQuery may attempt to cancel this work automatically.
//
// This deadline cannot be adjusted or removed once the job is created. Consider
// using Job.Cancel in situations where you need more dynamic behavior.
//
// Experimental: this option is experimental and may be modified or removed in future versions,
// regardless of any other documented package stability guarantees.
JobTimeout time.Duration
}
ExtractConfig holds the configuration for an extract job.
ExtractStatistics
type ExtractStatistics struct {
// The number of files per destination URI or URI pattern specified in the
// extract configuration. These values will be in the same order as the
// URIs specified in the 'destinationUris' field.
DestinationURIFileCounts []int64
}
ExtractStatistics contains statistics about an extract job.
Extractor
type Extractor struct {
JobIDConfig
ExtractConfig
// contains filtered or unexported fields
}
An Extractor extracts data from a BigQuery table into Google Cloud Storage.
func (*Extractor) Run
Run initiates an extract job.
FieldSchema
type FieldSchema struct {
// The field name.
// Must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_),
// and must start with a letter or underscore.
// The maximum length is 128 characters.
Name string
// A description of the field. The maximum length is 16,384 characters.
Description string
// Whether the field may contain multiple values.
Repeated bool
// Whether the field is required. Ignored if Repeated is true.
Required bool
// The field data type. If Type is Record, then this field contains a nested schema,
// which is described by Schema.
Type FieldType
// Annotations for enforcing column-level security constraints.
PolicyTags *PolicyTagList
// Describes the nested schema if Type is set to Record.
Schema Schema
// Maximum length of the field for STRING or BYTES type.
//
// It is invalid to set value for types other than STRING or BYTES.
//
// For STRING type, this represents the maximum UTF-8 length of strings
// allowed in the field. For BYTES type, this represents the maximum
// number of bytes in the field.
MaxLength int64
// Precision can be used to constrain the maximum number of
// total digits allowed for NUMERIC or BIGNUMERIC types.
//
// It is invalid to set values for Precision for types other than
// NUMERIC or BIGNUMERIC.
//
// For NUMERIC type, acceptable values for Precision must
// be: 1 ≤ (Precision - Scale) ≤ 29. Values for Scale
// must be: 0 ≤ Scale ≤ 9.
//
// For BIGNUMERIC type, acceptable values for Precision must
// be: 1 ≤ (Precision - Scale) ≤ 38. Values for Scale
// must be: 0 ≤ Scale ≤ 38.
Precision int64
// Scale can be used to constrain the maximum number of digits
// in the fractional part of a NUMERIC or BIGNUMERIC type.
//
// If the Scale value is set, the Precision value must be set as well.
//
// It is invalid to set values for Scale for types other than
// NUMERIC or BIGNUMERIC.
//
// See the Precision field for additional guidance about valid values.
Scale int64
// DefaultValueExpression is used to specify the default value of a field
// using a SQL expression. It can only be set for top level fields (columns).
//
// You can use struct or array expression to specify default value for the
// entire struct or array. The valid SQL expressions are:
//
// - Literals for all data types, including STRUCT and ARRAY.
// - The following functions:
// - CURRENT_TIMESTAMP
// - CURRENT_TIME
// - CURRENT_DATE
// - CURRENT_DATETIME
// - GENERATE_UUID
// - RAND
// - SESSION_USER
// - ST_GEOGPOINT
// - Struct or array composed with the above allowed functions, for example:
// [CURRENT_DATE(), DATE '2020-01-01']"
DefaultValueExpression string
// Collation can be set only when the type of field is STRING.
// The following values are supported:
// - 'und:ci': undetermined locale, case insensitive.
// - '': empty string. Default to case-sensitive behavior.
// More information: https://cloud.google.com/bigquery/docs/reference/standard-sql/collation-concepts
Collation string
// Information about the range.
// If the type is RANGE, this field is required.
RangeElementType *RangeElementType
// RoundingMode specifies the rounding mode to be used when storing
// values of NUMERIC and BIGNUMERIC type.
// If unspecified, default value is RoundHalfAwayFromZero.
RoundingMode RoundingMode
}
FieldSchema describes a single field.
FieldType
type FieldType string
FieldType is the type of field.
StringFieldType, BytesFieldType, IntegerFieldType, FloatFieldType, BooleanFieldType, TimestampFieldType, RecordFieldType, DateFieldType, TimeFieldType, DateTimeFieldType, NumericFieldType, GeographyFieldType, BigNumericFieldType, IntervalFieldType, JSONFieldType, RangeFieldType
const (
// StringFieldType is a string field type.
StringFieldType FieldType = "STRING"
// BytesFieldType is a bytes field type.
BytesFieldType FieldType = "BYTES"
// IntegerFieldType is a integer field type.
IntegerFieldType FieldType = "INTEGER"
// FloatFieldType is a float field type.
FloatFieldType FieldType = "FLOAT"
// BooleanFieldType is a boolean field type.
BooleanFieldType FieldType = "BOOLEAN"
// TimestampFieldType is a timestamp field type.
TimestampFieldType FieldType = "TIMESTAMP"
// RecordFieldType is a record field type. It is typically used to create columns with repeated or nested data.
RecordFieldType FieldType = "RECORD"
// DateFieldType is a date field type.
DateFieldType FieldType = "DATE"
// TimeFieldType is a time field type.
TimeFieldType FieldType = "TIME"
// DateTimeFieldType is a datetime field type.
DateTimeFieldType FieldType = "DATETIME"
// NumericFieldType is a numeric field type. Numeric types include integer types, floating point types and the
// NUMERIC data type.
NumericFieldType FieldType = "NUMERIC"
// GeographyFieldType is a string field type. Geography types represent a set of points
// on the Earth's surface, represented in Well Known Text (WKT) format.
GeographyFieldType FieldType = "GEOGRAPHY"
// BigNumericFieldType is a numeric field type that supports values of larger precision
// and scale than the NumericFieldType.
BigNumericFieldType FieldType = "BIGNUMERIC"
// IntervalFieldType is a representation of a duration or an amount of time.
IntervalFieldType FieldType = "INTERVAL"
// JSONFieldType is a representation of a json object.
JSONFieldType FieldType = "JSON"
// RangeFieldType represents a continuous range of values.
RangeFieldType FieldType = "RANGE"
)
FileConfig
type FileConfig struct {
// SourceFormat is the format of the data to be read.
// Allowed values are: Avro, CSV, DatastoreBackup, JSON, ORC, and Parquet. The default is CSV.
SourceFormat DataFormat
// Indicates if we should automatically infer the options and
// schema for CSV and JSON sources.
AutoDetect bool
// MaxBadRecords is the maximum number of bad records that will be ignored
// when reading data.
MaxBadRecords int64
// IgnoreUnknownValues causes values not matching the schema to be
// tolerated. Unknown values are ignored. For CSV this ignores extra values
// at the end of a line. For JSON this ignores named values that do not
// match any column name. If this field is not set, records containing
// unknown values are treated as bad records. The MaxBadRecords field can
// be used to customize how bad records are handled.
IgnoreUnknownValues bool
// Schema describes the data. It is required when reading CSV or JSON data,
// unless the data is being loaded into a table that already exists.
Schema Schema
// Additional options for CSV files.
CSVOptions
// Additional options for Parquet files.
ParquetOptions *ParquetOptions
// Additional options for Avro files.
AvroOptions *AvroOptions
}
FileConfig contains configuration options that pertain to files, typically text files that require interpretation to be used as a BigQuery table. A file may live in Google Cloud Storage (see GCSReference), or it may be loaded into a table via the Table.LoaderFromReader.
ForeignKey
type ForeignKey struct {
// Foreign key constraint name.
Name string
// Table that holds the primary key and is referenced by this foreign key.
ReferencedTable *Table
// Columns that compose the foreign key.
ColumnReferences []*ColumnReference
}
ForeignKey represents a foreign key constraint on a table's columns.
GCSReference
type GCSReference struct {
// URIs refer to Google Cloud Storage objects.
URIs []string
FileConfig
// DestinationFormat is the format to use when writing exported files.
// Allowed values are: CSV, Avro, JSON. The default is CSV.
// CSV is not supported for tables with nested or repeated fields.
DestinationFormat DataFormat
// Compression specifies the type of compression to apply when writing data
// to Google Cloud Storage, or using this GCSReference as an ExternalData
// source with CSV or JSON SourceFormat. Default is None.
//
// Avro files allow additional compression types: DEFLATE and SNAPPY.
Compression Compression
}
GCSReference is a reference to one or more Google Cloud Storage objects, which together constitute an input or output to a BigQuery operation.
func NewGCSReference
func NewGCSReference(uri string) *GCSReference
NewGCSReference constructs a reference to one or more Google Cloud Storage objects, which together constitute a data source or destination. In the simple case, a single URI in the form gs://bucket/object may refer to a single GCS object. Data may also be split into mutiple files, if multiple URIs or URIs containing wildcards are provided. Each URI may contain one '*' wildcard character, which (if present) must come after the bucket name. For more information about the treatment of wildcards and multiple URIs, see https://cloud.google.com/bigquery/exporting-data-from-bigquery#exportingmultiple
Example
package main
import (
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
gcsRef := bigquery.NewGCSReference("gs://my-bucket/my-object")
fmt.Println(gcsRef)
}
GoogleSheetsOptions
type GoogleSheetsOptions struct {
// The number of rows at the top of a sheet that BigQuery will skip when
// reading data.
SkipLeadingRows int64
// Optionally specifies a more specific range of cells to include.
// Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id
//
// Example: sheet1!A1:B20
Range string
}
GoogleSheetsOptions are additional options for GoogleSheets external data sources.
HivePartitioningMode
type HivePartitioningMode string
HivePartitioningMode is used in conjunction with HivePartitioningOptions.
AutoHivePartitioningMode, StringHivePartitioningMode, CustomHivePartitioningMode
const (
// AutoHivePartitioningMode automatically infers partitioning key and types.
AutoHivePartitioningMode HivePartitioningMode = "AUTO"
// StringHivePartitioningMode automatically infers partitioning keys and treats values as string.
StringHivePartitioningMode HivePartitioningMode = "STRINGS"
// CustomHivePartitioningMode allows custom definition of the external partitioning.
CustomHivePartitioningMode HivePartitioningMode = "CUSTOM"
)
HivePartitioningOptions
type HivePartitioningOptions struct {
// Mode defines which hive partitioning mode to use when reading data.
Mode HivePartitioningMode
// When hive partition detection is requested, a common prefix for
// all source uris should be supplied. The prefix must end immediately
// before the partition key encoding begins.
//
// For example, consider files following this data layout.
// gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro
// gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro
//
// When hive partitioning is requested with either AUTO or STRINGS
// detection, the common prefix can be either of
// gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing
// slash does not matter).
SourceURIPrefix string
// If set to true, queries against this external table require
// a partition filter to be present that can perform partition
// elimination. Hive-partitioned load jobs with this field
// set to true will fail.
RequirePartitionFilter bool
}
HivePartitioningOptions defines the behavior of Hive partitioning when working with external data.
IdentifierFormat
type IdentifierFormat string
IdentifierFormat represents a how certain resource identifiers such as table references are formatted.
StandardSQLID, LegacySQLID, StorageAPIResourceID, ErrUnknownIdentifierFormat
var (
// StandardSQLID returns an identifier suitable for use with Standard SQL.
StandardSQLID IdentifierFormat = "SQL"
// LegacySQLID returns an identifier suitable for use with Legacy SQL.
LegacySQLID IdentifierFormat = "LEGACY_SQL"
// StorageAPIResourceID returns an identifier suitable for use with the Storage API. Namely, it's for formatting
// a table resource for invoking read and write functionality.
StorageAPIResourceID IdentifierFormat = "STORAGE_API_RESOURCE"
// ErrUnknownIdentifierFormat is indicative of requesting an identifier in a format that is
// not supported.
ErrUnknownIdentifierFormat = errors.New("unknown identifier format")
)
Inserter
type Inserter struct {
// SkipInvalidRows causes rows containing invalid data to be silently
// ignored. The default value is false, which causes the entire request to
// fail if there is an attempt to insert an invalid row.
SkipInvalidRows bool
// IgnoreUnknownValues causes values not matching the schema to be ignored.
// The default value is false, which causes records containing such values
// to be treated as invalid records.
IgnoreUnknownValues bool
// A TableTemplateSuffix allows Inserters to create tables automatically.
//
// Experimental: this option is experimental and may be modified or removed in future versions,
// regardless of any other documented package stability guarantees. In general,
// the BigQuery team recommends the use of partitioned tables over sharding
// tables by suffix.
//
// When you specify a suffix, the table you upload data to
// will be used as a template for creating a new table, with the same schema,
// called +
An Inserter does streaming inserts into a BigQuery table. It is safe for concurrent use.
func (*Inserter) Put
Put uploads one or more rows to the BigQuery service.
If src is ValueSaver, then its Save method is called to produce a row for uploading.
If src is a struct or pointer to a struct, then a schema is inferred from it and used to create a StructSaver. The InsertID of the StructSaver will be empty.
If src is a slice of ValueSavers, structs, or struct pointers, then each element of the slice is treated as above, and multiple rows are uploaded.
Put returns a PutMultiError if one or more rows failed to be uploaded. The PutMultiError contains a RowInsertionError for each failed row.
Put will retry on temporary errors (see https://cloud.google.com/bigquery/troubleshooting-errors). This can result in duplicate rows if you do not use insert IDs. Also, if the error persists, the call will run indefinitely. Pass a context with a timeout to prevent hanging calls.
Examples
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
type Item struct {
Name string
Size float64
Count int
}
// Save implements the ValueSaver interface.
func (i *Item) Save() (map[string]bigquery.Value, string, error) {
return map[string]bigquery.Value{
"Name": i.Name,
"Size": i.Size,
"Count": i.Count,
}, "", nil
}
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ins := client.Dataset("my_dataset").Table("my_table").Inserter()
// Item implements the ValueSaver interface.
items := []*Item{
{Name: "n1", Size: 32.6, Count: 7},
{Name: "n2", Size: 4, Count: 2},
{Name: "n3", Size: 101.5, Count: 1},
}
if err := ins.Put(ctx, items); err != nil {
// TODO: Handle error.
}
}
struct
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ins := client.Dataset("my_dataset").Table("my_table").Inserter()
type score struct {
Name string
Num int
}
scores := []score{
{Name: "n1", Num: 12},
{Name: "n2", Num: 31},
{Name: "n3", Num: 7},
}
// Schema is inferred from the score type.
if err := ins.Put(ctx, scores); err != nil {
// TODO: Handle error.
}
}
structSaver
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
var schema bigquery.Schema
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ins := client.Dataset("my_dataset").Table("my_table").Inserter()
type score struct {
Name string
Num int
}
// Assume schema holds the table's schema.
savers := []*bigquery.StructSaver{
{Struct: score{Name: "n1", Num: 12}, Schema: schema, InsertID: "id1"},
{Struct: score{Name: "n2", Num: 31}, Schema: schema, InsertID: "id2"},
{Struct: score{Name: "n3", Num: 7}, Schema: schema, InsertID: "id3"},
}
if err := ins.Put(ctx, savers); err != nil {
// TODO: Handle error.
}
}
valuesSaver
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
var schema bigquery.Schema
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ins := client.Dataset("my_dataset").Table("my_table").Inserter()
var vss []*bigquery.ValuesSaver
for i, name := range []string{"n1", "n2", "n3"} {
// Assume schema holds the table's schema.
vss = append(vss, &bigquery.ValuesSaver{
Schema: schema,
InsertID: name,
Row: []bigquery.Value{name, int64(i)},
})
}
if err := ins.Put(ctx, vss); err != nil {
// TODO: Handle error.
}
}
IntervalValue
type IntervalValue struct {
// In canonical form, Years and Months share a consistent sign and reduced
// to avoid large month values.
Years int32
Months int32
// In canonical form, Days are independent of the other parts and can have it's
// own sign. There is no attempt to reduce larger Day values into the Y-M part.
Days int32
// In canonical form, the time parts all share a consistent sign and are reduced.
Hours int32
Minutes int32
Seconds int32
// This represents the fractional seconds as nanoseconds.
SubSecondNanos int32
}
IntervalValue is a go type for representing BigQuery INTERVAL values. Intervals are represented using three distinct parts:
- Years and Months
- Days
- Time (Hours/Mins/Seconds/Fractional Seconds).
More information about BigQuery INTERVAL types can be found at: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#interval_type
IntervalValue is EXPERIMENTAL and subject to change or removal without notice.
func IntervalValueFromDuration
func IntervalValueFromDuration(in time.Duration) *IntervalValue
IntervalValueFromDuration converts a time.Duration to an IntervalType representation.
The converted duration only leverages the hours/minutes/seconds part of the interval, the other parts representing days, months, and years are not used.
func ParseInterval
func ParseInterval(value string) (*IntervalValue, error)
ParseInterval parses an interval in canonical string format and returns the IntervalValue it represents.
func (*IntervalValue) Canonicalize
func (iv *IntervalValue) Canonicalize() *IntervalValue
Canonicalize returns an IntervalValue where signs for elements in the Y-M and H:M:S.F are consistent and values are normalized/reduced.
Canonical form enables more consistent comparison of the encoded interval. For example, encoding an interval with 12 months is equivalent to an interval of 1 year.
func (*IntervalValue) IsCanonical
func (iv *IntervalValue) IsCanonical() bool
IsCanonical evaluates whether the current representation is in canonical form.
func (*IntervalValue) String
func (iv *IntervalValue) String() string
String returns string representation of the interval value using the canonical format. The canonical format is as follows:
[sign]Y-M [sign]D [sign]H:M:S[.F]
func (*IntervalValue) ToDuration
func (iv *IntervalValue) ToDuration() time.Duration
ToDuration converts an interval to a time.Duration value.
For the purposes of conversion: Years are normalized to 12 months. Months are normalized to 30 days. Days are normalized to 24 hours.
Job
type Job struct {
// contains filtered or unexported fields
}
A Job represents an operation which has been submitted to BigQuery for processing.
func (*Job) Cancel
Cancel requests that a job be cancelled. This method returns without waiting for cancellation to take effect. To check whether the job has terminated, use Job.Status. Cancelled jobs may still incur costs.
func (*Job) Children
func (j *Job) Children(ctx context.Context) *JobIterator
Children returns a job iterator for enumerating child jobs of the current job. Currently only scripts, a form of query job, will create child jobs.
func (*Job) Config
Config returns the configuration information for j.
Example
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ds := client.Dataset("my_dataset")
job, err := ds.Table("t1").CopierFrom(ds.Table("t2")).Run(ctx)
if err != nil {
// TODO: Handle error.
}
jc, err := job.Config()
if err != nil {
// TODO: Handle error.
}
copyConfig := jc.(*bigquery.CopyConfig)
fmt.Println(copyConfig.Dst, copyConfig.CreateDisposition)
}
func (*Job) Delete
Delete deletes the job.
func (*Job) Email
Email returns the email of the job's creator.
func (*Job) ID
ID returns the job's ID.
func (*Job) LastStatus
LastStatus returns the most recently retrieved status of the job. The status is retrieved when a new job is created, or when JobFromID or Job.Status is called. Call Job.Status to get the most up-to-date information about a job.
func (*Job) Location
Location returns the job's location.
func (*Job) ProjectID
ProjectID returns the job's associated project.
func (*Job) Read
func (j *Job) Read(ctx context.Context) (ri *RowIterator, err error)
Read fetches the results of a query job. If j is not a query job, Read returns an error.
Example
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
q := client.Query("select name, num from t1")
// Call Query.Run to get a Job, then call Read on the job.
// Note: Query.Read is a shorthand for this.
job, err := q.Run(ctx)
if err != nil {
// TODO: Handle error.
}
it, err := job.Read(ctx)
if err != nil {
// TODO: Handle error.
}
_ = it // TODO: iterate using Next or iterator.Pager.
}
func (*Job) Status
Status retrieves the current status of the job from BigQuery. It fails if the Status could not be determined.
func (*Job) Wait
Wait blocks until the job or the context is done. It returns the final status of the job. If an error occurs while retrieving the status, Wait returns that error. But Wait returns nil if the status was retrieved successfully, even if status.Err() != nil. So callers must check both errors. See the example.
Example
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
ds := client.Dataset("my_dataset")
job, err := ds.Table("t1").CopierFrom(ds.Table("t2")).Run(ctx)
if err != nil {
// TODO: Handle error.
}
status, err := job.Wait(ctx)
if err != nil {
// TODO: Handle error.
}
if status.Err() != nil {
// TODO: Handle error.
}
}
JobConfig
type JobConfig interface {
// contains filtered or unexported methods
}
JobConfig contains configuration information for a job. It is implemented by *CopyConfig, *ExtractConfig, *LoadConfig and *QueryConfig.
JobIDConfig
type JobIDConfig struct {
// JobID is the ID to use for the job. If empty, a random job ID will be generated.
JobID string
// If AddJobIDSuffix is true, then a random string will be appended to JobID.
AddJobIDSuffix bool
// Location is the location for the job.
Location string
// ProjectID is the Google Cloud project associated with the job.
ProjectID string
}
JobIDConfig describes how to create an ID for a job.
JobIterator
type JobIterator struct {
ProjectID string // Project ID of the jobs to list. Default is the client's project.
AllUsers bool // Whether to list jobs owned by all users in the project, or just the current caller.
State State // List only jobs in the given state. Defaults to all states.
MinCreationTime time.Time // List only jobs created after this time.
MaxCreationTime time.Time // List only jobs created before this time.
ParentJobID string // List only jobs that are children of a given scripting job.
// contains filtered or unexported fields
}
JobIterator iterates over jobs in a project.
func (*JobIterator) Next
func (it *JobIterator) Next() (*Job, error)
Next returns the next Job. Its second return value is iterator.Done if there are no more results. Once Next returns Done, all subsequent calls will return Done.
func (*JobIterator) PageInfo
func (it *JobIterator) PageInfo() *iterator.PageInfo
PageInfo is a getter for the JobIterator's PageInfo.
JobStatistics
type JobStatistics struct {
CreationTime time.Time
StartTime time.Time
EndTime time.Time
TotalBytesProcessed int64
Details Statistics
// NumChildJobs indicates the number of child jobs run as part of a script.
NumChildJobs int64
// ParentJobID indicates the origin job for jobs run as part of a script.
ParentJobID string
// ScriptStatistics includes information run as part of a child job within
// a script.
ScriptStatistics *ScriptStatistics
// ReservationUsage attributes slot consumption to reservations.
ReservationUsage []*ReservationUsage
// TransactionInfo indicates the transaction ID associated with the job, if any.
TransactionInfo *TransactionInfo
// SessionInfo contains information about the session if this job is part of one.
SessionInfo *SessionInfo
}
JobStatistics contains statistics about a job.
JobStatus
type JobStatus struct {
State State
// All errors encountered during the running of the job.
// Not all Errors are fatal, so errors here do not necessarily mean that the job has completed or was unsuccessful.
Errors []*Error
// Statistics about the job.
Statistics *JobStatistics
// contains filtered or unexported fields
}
JobStatus contains the current State of a job, and errors encountered while processing that job.
func (*JobStatus) Done
Done reports whether the job has completed. After Done returns true, the Err method will return an error if the job completed unsuccessfully.
func (*JobStatus) Err
Err returns the error that caused the job to complete unsuccessfully (if any).
LoadConfig
type LoadConfig struct {
// Src is the source from which data will be loaded.
Src LoadSource
// Dst is the table into which the data will be loaded.
Dst *Table
// CreateDisposition specifies the circumstances under which the destination table will be created.
// The default is CreateIfNeeded.
CreateDisposition TableCreateDisposition
// WriteDisposition specifies how existing data in the destination table is treated.
// The default is WriteAppend.
WriteDisposition TableWriteDisposition
// The labels associated with this job.
Labels map[string]string
// If non-nil, the destination table is partitioned by time.
TimePartitioning *TimePartitioning
// If non-nil, the destination table is partitioned by integer range.
RangePartitioning *RangePartitioning
// Clustering specifies the data clustering configuration for the destination table.
Clustering *Clustering
// Custom encryption configuration (e.g., Cloud KMS keys).
DestinationEncryptionConfig *EncryptionConfig
// Allows the schema of the destination table to be updated as a side effect of
// the load job.
SchemaUpdateOptions []string
// For Avro-based loads, controls whether logical type annotations are used.
// See https://cloud.google.com/bigquery/docs/loading-data-cloud-storage-avro#logical_types
// for additional information.
UseAvroLogicalTypes bool
// For ingestion from datastore backups, ProjectionFields governs which fields
// are projected from the backup. The default behavior projects all fields.
ProjectionFields []string
// HivePartitioningOptions allows use of Hive partitioning based on the
// layout of objects in Cloud Storage.
HivePartitioningOptions *HivePartitioningOptions
// DecimalTargetTypes allows selection of how decimal values are converted when
// processed in bigquery, subject to the value type having sufficient precision/scale
// to support the values. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is
// selected if is present in the list and if supports the necessary precision and scale.
//
// StringTargetType supports all precision and scale values.
DecimalTargetTypes []DecimalTargetType
// Sets a best-effort deadline on a specific job. If job execution exceeds this
// timeout, BigQuery may attempt to cancel this work automatically.
//
// This deadline cannot be adjusted or removed once the job is created. Consider
// using Job.Cancel in situations where you need more dynamic behavior.
//
// Experimental: this option is experimental and may be modified or removed in future versions,
// regardless of any other documented package stability guarantees.
JobTimeout time.Duration
// When loading a table with external data, the user can provide a reference file with the table schema.
// This is enabled for the following formats: AVRO, PARQUET, ORC.
ReferenceFileSchemaURI string
// If true, creates a new session, where session id will
// be a server generated random id. If false, runs query with an
// existing session_id passed in ConnectionProperty, otherwise runs the
// load job in non-session mode.
CreateSession bool
// ConnectionProperties are optional key-values settings.
ConnectionProperties []*ConnectionProperty
// MediaOptions stores options for customizing media upload.
MediaOptions []googleapi.MediaOption
// Controls the behavior of column naming during a load job.
// For more information, see:
// https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#columnnamecharactermap
ColumnNameCharacterMap ColumnNameCharacterMap
}
LoadConfig holds the configuration for a load job.
LoadSource
type LoadSource interface {
// contains filtered or unexported methods
}
A LoadSource represents a source of data that can be loaded into a BigQuery table.
This package defines two LoadSources: GCSReference, for Google Cloud Storage objects, and ReaderSource, for data read from an io.Reader.
LoadStatistics
type LoadStatistics struct {
// The number of bytes of source data in a load job.
InputFileBytes int64
// The number of source files in a load job.
InputFiles int64
// Size of the loaded data in bytes. Note that while a load job is in the
// running state, this value may change.
OutputBytes int64
// The number of rows imported in a load job. Note that while an import job is
// in the running state, this value may change.
OutputRows int64
}
LoadStatistics contains statistics about a load job.
Loader
type Loader struct {
JobIDConfig
LoadConfig
// contains filtered or unexported fields
}
A Loader loads data from Google Cloud Storage into a BigQuery table.
func (*Loader) Run
Run initiates a load job.
MaterializedViewDefinition
type MaterializedViewDefinition struct {
// EnableRefresh governs whether the derived view is updated to reflect
// changes in the base table.
EnableRefresh bool
// LastRefreshTime reports the time, in millisecond precision, that the
// materialized view was last updated.
LastRefreshTime time.Time
// Query contains the SQL query used to define the materialized view.
Query string
// RefreshInterval defines the maximum frequency, in millisecond precision,
// at which this this materialized view will be refreshed.
RefreshInterval time.Duration
// AllowNonIncrementalDefinition for materialized view definition.
// The default value is false.
AllowNonIncrementalDefinition bool
// MaxStaleness of data that could be returned when materialized
// view is queried.
MaxStaleness *IntervalValue
}
MaterializedViewDefinition contains information for materialized views.
Model
type Model struct {
ProjectID string
DatasetID string
// ModelID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_).
// The maximum length is 1,024 characters.
ModelID string
// contains filtered or unexported fields
}
Model represent a reference to a BigQuery ML model. Within the API, models are used largely for communicating statistical information about a given model, as creation of models is only supported via BigQuery queries (e.g. CREATE MODEL .. AS ..).
For more info, see documentation for Bigquery ML, see: https://cloud.google.com/bigquery/docs/bigqueryml
func (*Model) Delete
Delete deletes an ML model.
func (*Model) ExtractorTo
func (m *Model) ExtractorTo(dst *GCSReference) *Extractor
ExtractorTo returns an Extractor which can be persist a BigQuery Model into Google Cloud Storage. The returned Extractor may be further configured before its Run method is called.
func (*Model) FullyQualifiedName
FullyQualifiedName returns the ID of the model in projectID:datasetID.modelid format.
func (*Model) Identifier
func (m *Model) Identifier(f IdentifierFormat) (string, error)
Identifier returns the ID of the model in the requested format.
For Standard SQL format, the identifier will be quoted if the ProjectID contains dash (-) characters.
func (*Model) Metadata
func (m *Model) Metadata(ctx context.Context) (mm *ModelMetadata, err error)
Metadata fetches the metadata for a model, which includes ML training statistics.
func (*Model) Update
func (m *Model) Update(ctx context.Context, mm ModelMetadataToUpdate, etag string) (md *ModelMetadata, err error)
Update updates mutable fields in an ML model.
ModelIterator
type ModelIterator struct {
// contains filtered or unexported fields
}
A ModelIterator is an iterator over Models.
func (*ModelIterator) Next
func (it *ModelIterator) Next() (*Model, error)
Next returns the next result. Its second return value is Done if there are no more results. Once Next returns Done, all subsequent calls will return Done.
func (*ModelIterator) PageInfo
func (it *ModelIterator) PageInfo() *iterator.PageInfo
PageInfo supports pagination. See the google.golang.org/api/iterator package for details.
ModelMetadata
type ModelMetadata struct {
// The user-friendly description of the model.
Description string
// The user-friendly name of the model.
Name string
// The type of the model. Possible values include:
// "LINEAR_REGRESSION" - a linear regression model
// "LOGISTIC_REGRESSION" - a logistic regression model
// "KMEANS" - a k-means clustering model
Type string
// The creation time of the model.
CreationTime time.Time
// The last modified time of the model.
LastModifiedTime time.Time
// The expiration time of the model.
ExpirationTime time.Time
// The geographic location where the model resides. This value is
// inherited from the encapsulating dataset.
Location string
// Custom encryption configuration (e.g., Cloud KMS keys).
EncryptionConfig *EncryptionConfig
Labels map[string]string
// ETag is the ETag obtained when reading metadata. Pass it to Model.Update
// to ensure that the metadata hasn't changed since it was read.
ETag string
// contains filtered or unexported fields
}
ModelMetadata represents information about a BigQuery ML model.
func (*ModelMetadata) RawFeatureColumns
func (mm *ModelMetadata) RawFeatureColumns() ([]*StandardSQLField, error)
RawFeatureColumns exposes the underlying feature columns used to train an ML model and uses types from "google.golang.org/api/bigquery/v2", which are subject to change without warning. It is EXPERIMENTAL and subject to change or removal without notice.
func (*ModelMetadata) RawLabelColumns
func (mm *ModelMetadata) RawLabelColumns() ([]*StandardSQLField, error)
RawLabelColumns exposes the underlying label columns used to train an ML model and uses types from "google.golang.org/api/bigquery/v2", which are subject to change without warning. It is EXPERIMENTAL and subject to change or removal without notice.
func (*ModelMetadata) RawTrainingRuns
func (mm *ModelMetadata) RawTrainingRuns() []*TrainingRun
RawTrainingRuns exposes the underlying training run stats for a model using types from "google.golang.org/api/bigquery/v2", which are subject to change without warning. It is EXPERIMENTAL and subject to change or removal without notice.
ModelMetadataToUpdate
type ModelMetadataToUpdate struct {
// The user-friendly description of this model.
Description optional.String
// The user-friendly name of this model.
Name optional.String
// The time when this model expires. To remove a model's expiration,
// set ExpirationTime to NeverExpire. The zero value is ignored.
ExpirationTime time.Time
// The model's encryption configuration.
EncryptionConfig *EncryptionConfig
// contains filtered or unexported fields
}
ModelMetadataToUpdate is used when updating an ML model's metadata. Only non-nil fields will be updated.
func (*ModelMetadataToUpdate) DeleteLabel
func (u *ModelMetadataToUpdate) DeleteLabel(name string)
DeleteLabel causes a label to be deleted on a call to Update.
func (*ModelMetadataToUpdate) SetLabel
func (u *ModelMetadataToUpdate) SetLabel(name, value string)
SetLabel causes a label to be added or modified on a call to Update.
MultiError
type MultiError []error
A MultiError contains multiple related errors.
func (MultiError) Error
func (m MultiError) Error() string
NullBool
NullBool represents a BigQuery BOOL that may be NULL.
func (NullBool) MarshalJSON
MarshalJSON converts the NullBool to JSON.
func (NullBool) String
func (*NullBool) UnmarshalJSON
UnmarshalJSON converts JSON into a NullBool.
NullDate
NullDate represents a BigQuery DATE that may be null.
func (NullDate) MarshalJSON
MarshalJSON converts the NullDate to JSON.
func (NullDate) String
func (*NullDate) UnmarshalJSON
UnmarshalJSON converts JSON into a NullDate.
NullDateTime
type NullDateTime struct {
DateTime civil.DateTime
Valid bool // Valid is true if DateTime is not NULL.
}
NullDateTime represents a BigQuery DATETIME that may be null.
func (NullDateTime) MarshalJSON
func (n NullDateTime) MarshalJSON() ([]byte, error)
MarshalJSON converts the NullDateTime to JSON.
func (NullDateTime) String
func (n NullDateTime) String() string
func (*NullDateTime) UnmarshalJSON
func (n *NullDateTime) UnmarshalJSON(b []byte) error
UnmarshalJSON converts JSON into a NullDateTime.
NullFloat64
NullFloat64 represents a BigQuery FLOAT64 that may be NULL.
func (NullFloat64) MarshalJSON
func (n NullFloat64) MarshalJSON() (b []byte, err error)
MarshalJSON converts the NullFloat64 to JSON.
func (NullFloat64) String
func (n NullFloat64) String() string
func (*NullFloat64) UnmarshalJSON
func (n *NullFloat64) UnmarshalJSON(b []byte) error
UnmarshalJSON converts JSON into a NullFloat64.
NullGeography
type NullGeography struct {
GeographyVal string
Valid bool // Valid is true if GeographyVal is not NULL.
}
NullGeography represents a BigQuery GEOGRAPHY string that may be NULL.
func (NullGeography) MarshalJSON
func (n NullGeography) MarshalJSON() ([]byte, error)
MarshalJSON converts the NullGeography to JSON.
func (NullGeography) String
func (n NullGeography) String() string
func (*NullGeography) UnmarshalJSON
func (n *NullGeography) UnmarshalJSON(b []byte) error
UnmarshalJSON converts JSON into a NullGeography.
NullInt64
NullInt64 represents a BigQuery INT64 that may be NULL.
func (NullInt64) MarshalJSON
MarshalJSON converts the NullInt64 to JSON.
func (NullInt64) String
func (*NullInt64) UnmarshalJSON
UnmarshalJSON converts JSON into a NullInt64.
NullJSON
NullJSON represents a BigQuery JSON string that may be NULL.
func (NullJSON) MarshalJSON
MarshalJSON converts the NullJSON to JSON.
func (NullJSON) String
func (*NullJSON) UnmarshalJSON
UnmarshalJSON converts JSON into a NullJSON.
NullString
NullString represents a BigQuery STRING that may be NULL.
func (NullString) MarshalJSON
func (n NullString) MarshalJSON() ([]byte, error)
MarshalJSON converts the NullString to JSON.
func (NullString) String
func (n NullString) String() string
func (*NullString) UnmarshalJSON
func (n *NullString) UnmarshalJSON(b []byte) error
UnmarshalJSON converts JSON into a NullString.
NullTime
NullTime represents a BigQuery TIME that may be null.
func (NullTime) MarshalJSON
MarshalJSON converts the NullTime to JSON.
func (NullTime) String
func (*NullTime) UnmarshalJSON
UnmarshalJSON converts JSON into a NullTime.
NullTimestamp
NullTimestamp represents a BigQuery TIMESTAMP that may be null.
func (NullTimestamp) MarshalJSON
func (n NullTimestamp) MarshalJSON() ([]byte, error)
MarshalJSON converts the NullTimestamp to JSON.
func (NullTimestamp) String
func (n NullTimestamp) String() string
func (*NullTimestamp) UnmarshalJSON
func (n *NullTimestamp) UnmarshalJSON(b []byte) error
UnmarshalJSON converts JSON into a NullTimestamp.
ParquetOptions
type ParquetOptions struct {
// EnumAsString indicates whether to infer Parquet ENUM logical type as
// STRING instead of BYTES by default.
EnumAsString bool
// EnableListInference indicates whether to use schema inference
// specifically for Parquet LIST logical type.
EnableListInference bool
}
ParquetOptions are additional options for Parquet external data sources.
PolicyTagList
type PolicyTagList struct {
Names []string
}
PolicyTagList represents the annotations on a schema column for enforcing column-level security. For more information, see https://cloud.google.com/bigquery/docs/column-level-security-intro
PrimaryKey
type PrimaryKey struct {
// Columns that compose the primary key constraint.
Columns []string
}
PrimaryKey represents the primary key constraint on a table's columns.
PutMultiError
type PutMultiError []RowInsertionError
PutMultiError contains an error for each row which was not successfully inserted into a BigQuery table.
func (PutMultiError) Error
func (pme PutMultiError) Error() string
Query
type Query struct {
JobIDConfig
QueryConfig
// contains filtered or unexported fields
}
A Query queries data from a BigQuery table. Use Client.Query to create a Query.
func (*Query) Read
func (q *Query) Read(ctx context.Context) (it *RowIterator, err error)
Read submits a query for execution and returns the results via a RowIterator. If the request can be satisfied by running using the optimized query path, it is used in place of the jobs.insert path as this path does not expose a job object.
Examples
package main
import (
"context"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
q := client.Query("select name, num from t1")
it, err := q.Read(ctx)
if err != nil {
// TODO: Handle error.
}
_ = it // TODO: iterate using Next or iterator.Pager.
}
accelerated
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
// Enable Storage API usage for fetching data
err = client.EnableStorageReadClient(ctx)
if err != nil {
// TODO: Handle error.
}
sql := fmt.Sprintf(`SELECT name, number, state FROM %s WHERE state = "CA"`, `bigquery-public-data.usa_names.usa_1910_current`)
q := client.Query(sql)
it, err := q.Read(ctx)
if err != nil {
// TODO: Handle error.
}
_ = it // TODO: iterate using Next or iterator.Pager.
}
func (*Query) Run
Run initiates a query job.
QueryConfig
type QueryConfig struct {
// Dst is the table into which the results of the query will be written.
// If this field is nil, a temporary table will be created.
Dst *Table
// The query to execute. See https://cloud.google.com/bigquery/query-reference for details.
Q string
// DefaultProjectID and DefaultDatasetID specify the dataset to use for unqualified table names in the query.
// If DefaultProjectID is set, DefaultDatasetID must also be set.
DefaultProjectID string
DefaultDatasetID string
// TableDefinitions describes data sources outside of BigQuery.
// The map keys may be used as table names in the query string.
//
// When a QueryConfig is returned from Job.Config, the map values
// are always of type *ExternalDataConfig.
TableDefinitions map[string]ExternalData
// CreateDisposition specifies the circumstances under which the destination table will be created.
// The default is CreateIfNeeded.
CreateDisposition TableCreateDisposition
// WriteDisposition specifies how existing data in the destination table is treated.
// The default is WriteEmpty.
WriteDisposition TableWriteDisposition
// DisableQueryCache prevents results being fetched from the query cache.
// If this field is false, results are fetched from the cache if they are available.
// The query cache is a best-effort cache that is flushed whenever tables in the query are modified.
// Cached results are only available when TableID is unspecified in the query's destination Table.
// For more information, see https://cloud.google.com/bigquery/querying-data#querycaching
DisableQueryCache bool
// DisableFlattenedResults prevents results being flattened.
// If this field is false, results from nested and repeated fields are flattened.
// DisableFlattenedResults implies AllowLargeResults
// For more information, see https://cloud.google.com/bigquery/docs/data#nested
DisableFlattenedResults bool
// AllowLargeResults allows the query to produce arbitrarily large result tables.
// The destination must be a table.
// When using this option, queries will take longer to execute, even if the result set is small.
// For additional limitations, see https://cloud.google.com/bigquery/querying-data#largequeryresults
AllowLargeResults bool
// Priority specifies the priority with which to schedule the query.
// The default priority is InteractivePriority.
// For more information, see https://cloud.google.com/bigquery/querying-data#batchqueries
Priority QueryPriority
// MaxBillingTier sets the maximum billing tier for a Query.
// Queries that have resource usage beyond this tier will fail (without
// incurring a charge). If this field is zero, the project default will be used.
MaxBillingTier int
// MaxBytesBilled limits the number of bytes billed for
// this job. Queries that would exceed this limit will fail (without incurring
// a charge).
// If this field is less than 1, the project default will be
// used.
MaxBytesBilled int64
// UseStandardSQL causes the query to use standard SQL. The default.
// Deprecated: use UseLegacySQL.
UseStandardSQL bool
// UseLegacySQL causes the query to use legacy SQL.
UseLegacySQL bool
// Parameters is a list of query parameters. The presence of parameters
// implies the use of standard SQL.
// If the query uses positional syntax ("?"), then no parameter may have a name.
// If the query uses named syntax ("@p"), then all parameters must have names.
// It is illegal to mix positional and named syntax.
Parameters []QueryParameter
// TimePartitioning specifies time-based partitioning
// for the destination table.
TimePartitioning *TimePartitioning
// RangePartitioning specifies integer range-based partitioning
// for the destination table.
RangePartitioning *RangePartitioning
// Clustering specifies the data clustering configuration for the destination table.
Clustering *Clustering
// The labels associated with this job.
Labels map[string]string
// If true, don't actually run this job. A valid query will return a mostly
// empty response with some processing statistics, while an invalid query will
// return the same error it would if it wasn't a dry run.
//
// Query.Read will fail with dry-run queries. Call Query.Run instead, and then
// call LastStatus on the returned job to get statistics. Calling Status on a
// dry-run job will fail.
DryRun bool
// Custom encryption configuration (e.g., Cloud KMS keys).
DestinationEncryptionConfig *EncryptionConfig
// Allows the schema of the destination table to be updated as a side effect of
// the query job.
SchemaUpdateOptions []string
// CreateSession will trigger creation of a new session when true.
CreateSession bool
// ConnectionProperties are optional key-values settings.
ConnectionProperties []*ConnectionProperty
// Sets a best-effort deadline on a specific job. If job execution exceeds this
// timeout, BigQuery may attempt to cancel this work automatically.
//
// This deadline cannot be adjusted or removed once the job is created. Consider
// using Job.Cancel in situations where you need more dynamic behavior.
//
// Experimental: this option is experimental and may be modified or removed in future versions,
// regardless of any other documented package stability guarantees.
JobTimeout time.Duration
// contains filtered or unexported fields
}
QueryConfig holds the configuration for a query job.
QueryParameter
type QueryParameter struct {
// Name is used for named parameter mode.
// It must match the name in the query case-insensitively.
Name string
// Value is the value of the parameter.
//
// When you create a QueryParameter to send to BigQuery, the following Go types
// are supported, with their corresponding Bigquery types:
// int, int8, int16, int32, int64, uint8, uint16, uint32: INT64
// Note that uint, uint64 and uintptr are not supported, because
// they may contain values that cannot fit into a 64-bit signed integer.
// float32, float64: FLOAT64
// bool: BOOL
// string: STRING
// []byte: BYTES
// time.Time: TIMESTAMP
// *big.Rat: NUMERIC
// *IntervalValue: INTERVAL
// Arrays and slices of the above.
// Structs of the above. Only the exported fields are used.
//
// For scalar values, you can supply the Null types within this library
// to send the appropriate NULL values (e.g. NullInt64, NullString, etc).
//
// To specify query parameters explicitly rather by inference, *QueryParameterValue can be used.
// For example, a BIGNUMERIC can be specified like this:
// &QueryParameterValue{
// Type: StandardSQLDataType{
// TypeKind: "BIGNUMERIC",
// },
// Value: BigNumericString(*big.Rat),
// }
//
// When a QueryParameter is returned inside a QueryConfig from a call to
// Job.Config:
// Integers are of type int64.
// Floating-point values are of type float64.
// Arrays are of type []interface{}, regardless of the array element type.
// Structs are of type map[string]interface{}.
//
// When valid (non-null) Null types are sent, they come back as the Go types indicated
// above. Null strings will report in query statistics as a valid empty
// string.
Value interface{}
}
A QueryParameter is a parameter to a query.
QueryParameterValue
type QueryParameterValue struct {
// Type specifies the parameter type. See StandardSQLDataType for more.
// Scalar parameters and more complex types can be defined within this field.
// See examples on the value fields.
Type StandardSQLDataType
// Value is the value of the parameter, if a simple scalar type.
// The default behavior for scalar values is to do type inference
// and format it accordingly.
// Because of that, depending on the parameter type, is recommended
// to send value as a String.
// We provide some formatter functions for some types:
// CivilTimeString(civil.Time)
// CivilDateTimeString(civil.DateTime)
// NumericString(*big.Rat)
// BigNumericString(*big.Rat)
// IntervalString(*IntervalValue)
//
// Example:
//
// &QueryParameterValue{
// Type: StandardSQLDataType{
// TypeKind: "BIGNUMERIC",
// },
// Value: BigNumericString(*big.Rat),
// }
Value interface{}
// ArrayValue is the array of values for the parameter.
//
// Must be used with QueryParameterValue.Type being a StandardSQLDataType
// with ArrayElementType filled with the given element type.
//
// Example of an array of strings :
// &QueryParameterValue{
// Type: &StandardSQLDataType{
// ArrayElementType: &StandardSQLDataType{
// TypeKind: "STRING",
// },
// },
// ArrayValue: []QueryParameterValue{
// {Value: "a"},
// {Value: "b"},
// },
// }
//
// Example of an array of structs :
// &QueryParameterValue{
// Type: &StandardSQLDataType{
// ArrayElementType: &StandardSQLDataType{
// StructType: &StandardSQLDataType{
// Fields: []*StandardSQLField{
// {
// Name: "NumberField",
// Type: &StandardSQLDataType{
// TypeKind: "INT64",
// },
// },
// },
// },
// },
// },
// ArrayValue: []QueryParameterValue{
// {StructValue: map[string]QueryParameterValue{
// "NumberField": {
// Value: int64(42),
// },
// }},
// {StructValue: map[string]QueryParameterValue{
// "NumberField": {
// Value: int64(43),
// },
// }},
// },
// }
ArrayValue []QueryParameterValue
// StructValue is the struct field values for the parameter.
//
// Must be used with QueryParameterValue.Type being a StandardSQLDataType
// with StructType filled with the given field types.
//
// Example:
//
// &QueryParameterValue{
// Type: &StandardSQLDataType{
// StructType{
// Fields: []*StandardSQLField{
// {
// Name: "StringField",
// Type: &StandardSQLDataType{
// TypeKind: "STRING",
// },
// },
// {
// Name: "NumberField",
// Type: &StandardSQLDataType{
// TypeKind: "INT64",
// },
// },
// },
// },
// },
// StructValue: []map[string]QueryParameterValue{
// "NumberField": {
// Value: int64(42),
// },
// "StringField": {
// Value: "Value",
// },
// },
// }
StructValue map[string]QueryParameterValue
}
QueryParameterValue is a go type for representing a explicit typed QueryParameter.
QueryPriority
type QueryPriority string
QueryPriority specifies a priority with which a query is to be executed.
BatchPriority, InteractivePriority
const (
// BatchPriority specifies that the query should be scheduled with the
// batch priority. BigQuery queues each batch query on your behalf, and
// starts the query as soon as idle resources are available, usually within
// a few minutes. If BigQuery hasn't started the query within 24 hours,
// BigQuery changes the job priority to interactive. Batch queries don't
// count towards your concurrent rate limit, which can make it easier to
// start many queries at once.
//
// More information can be found at https://cloud.google.com/bigquery/docs/running-queries#batchqueries.
BatchPriority QueryPriority = "BATCH"
// InteractivePriority specifies that the query should be scheduled with
// interactive priority, which means that the query is executed as soon as
// possible. Interactive queries count towards your concurrent rate limit
// and your daily limit. It is the default priority with which queries get
// executed.
//
// More information can be found at https://cloud.google.com/bigquery/docs/running-queries#queries.
InteractivePriority QueryPriority = "INTERACTIVE"
)
QueryStatistics
type QueryStatistics struct {
// BI-Engine specific statistics.
BIEngineStatistics *BIEngineStatistics
// Billing tier for the job.
BillingTier int64
// Whether the query result was fetched from the query cache.
CacheHit bool
// The type of query statement, if valid.
StatementType string
// Total bytes billed for the job.
TotalBytesBilled int64
// Total bytes processed for the job.
TotalBytesProcessed int64
// For dry run queries, indicates how accurate the TotalBytesProcessed value is.
// When indicated, values include:
// UNKNOWN: accuracy of the estimate is unknown.
// PRECISE: estimate is precise.
// LOWER_BOUND: estimate is lower bound of what the query would cost.
// UPPER_BOUND: estimate is upper bound of what the query would cost.
TotalBytesProcessedAccuracy string
// Describes execution plan for the query.
QueryPlan []*ExplainQueryStage
// The number of rows affected by a DML statement. Present only for DML
// statements INSERT, UPDATE or DELETE.
NumDMLAffectedRows int64
// DMLStats provides statistics about the row mutations performed by
// DML statements.
DMLStats *DMLStatistics
// Describes a timeline of job execution.
Timeline []*QueryTimelineSample
// ReferencedTables: [Output-only] Referenced tables for
// the job. Queries that reference more than 50 tables will not have a
// complete list.
ReferencedTables []*Table
// The schema of the results. Present only for successful dry run of
// non-legacy SQL queries.
Schema Schema
// Slot-milliseconds consumed by this query job.
SlotMillis int64
// Standard SQL: list of undeclared query parameter names detected during a
// dry run validation.
UndeclaredQueryParameterNames []string
// DDL target table.
DDLTargetTable *Table
// DDL Operation performed on the target table. Used to report how the
// query impacted the DDL target table.
DDLOperationPerformed string
// The DDL target table, present only for CREATE/DROP FUNCTION/PROCEDURE queries.
DDLTargetRoutine *Routine
// Statistics for the EXPORT DATA statement as part of Query Job.
ExportDataStatistics *ExportDataStatistics
}
QueryStatistics contains statistics about a query job.
QueryTimelineSample
type QueryTimelineSample struct {
// Total number of units currently being processed by workers, represented as largest value since last sample.
ActiveUnits int64
// Total parallel units of work completed by this query.
CompletedUnits int64
// Time elapsed since start of query execution.
Elapsed time.Duration
// Total parallel units of work remaining for the active stages.
PendingUnits int64
// Cumulative slot-milliseconds consumed by the query.
SlotMillis int64
}
QueryTimelineSample represents a sample of execution statistics at a point in time.
RangeElementType
type RangeElementType struct {
// The subtype of the RANGE, if the type of this field is RANGE.
// Possible values for the field element type of a RANGE include:
// DATE, DATETIME, or TIMESTAMP.
Type FieldType
}
RangeElementType describes information about the range type.
RangePartitioning
type RangePartitioning struct {
// The field by which the table is partitioned.
// This field must be a top-level field, and must be typed as an
// INTEGER/INT64.
Field string
// The details of how partitions are mapped onto the integer range.
Range *RangePartitioningRange
}
RangePartitioning indicates an integer-range based storage organization strategy.
RangePartitioningRange
type RangePartitioningRange struct {
// The start value of defined range of values, inclusive of the specified value.
Start int64
// The end of the defined range of values, exclusive of the defined value.
End int64
// The width of each interval range.
Interval int64
}
RangePartitioningRange defines the boundaries and width of partitioned values.
RangeValue
type RangeValue struct {
// The start value of the range. A missing value represents an
// unbounded start.
Start Value `json:"start"`
// The end value of the range. A missing value represents an
// unbounded end.
End Value `json:"end"`
}
RangeValue represents a continuous RANGE of values of a given element type. The supported element types for RANGE are currently the BigQuery DATE, DATETIME, and TIMESTAMP, types.
ReaderSource
type ReaderSource struct {
FileConfig
// contains filtered or unexported fields
}
A ReaderSource is a source for a load operation that gets data from an io.Reader.
When a ReaderSource is part of a LoadConfig obtained via Job.Config, its internal io.Reader will be nil, so it cannot be used for a subsequent load operation.
func NewReaderSource
func NewReaderSource(r io.Reader) *ReaderSource
NewReaderSource creates a ReaderSource from an io.Reader. You may optionally configure properties on the ReaderSource that describe the data being read, before passing it to Table.LoaderFrom.
RemoteFunctionOptions
type RemoteFunctionOptions struct {
// Fully qualified name of the user-provided connection object which holds
// the authentication information to send requests to the remote service.
// Format:
// projects/{projectId}/locations/{locationId}/connections/{connectionId}
Connection string
// Endpoint of the user-provided remote service (e.g. a function url in
// Google Cloud Function or Cloud Run )
Endpoint string
// Max number of rows in each batch sent to the remote service.
// If absent or if 0, it means no limit.
MaxBatchingRows int64
// User-defined context as a set of key/value pairs,
// which will be sent as function invocation context together with
// batched arguments in the requests to the remote service. The total
// number of bytes of keys and values must be less than 8KB.
UserDefinedContext map[string]string
}
RemoteFunctionOptions contains information for a remote user-defined function.
ReservationUsage
type ReservationUsage struct {
// SlotMillis reports the slot milliseconds utilized within in the given reservation.
SlotMillis int64
// Name indicates the utilized reservation name, or "unreserved" for ondemand usage.
Name string
}
ReservationUsage contains information about a job's usage of a single reservation.
RoundingMode
type RoundingMode string
RoundingMode represents the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
RoundHalfAwayFromZero, RoundHalfEven
const (
// RoundHalfAwayFromZero rounds half values away from zero when applying
// precision and scale upon writing of NUMERIC and BIGNUMERIC values.
// For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5, 1.6, 1.7, 1.8, 1.9 => 2
RoundHalfAwayFromZero RoundingMode = "ROUND_HALF_AWAY_FROM_ZERO"
// RoundHalfEven rounds half values to the nearest even value when applying
// precision and scale upon writing of NUMERIC and BIGNUMERIC values.
// For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5 => 2 1.6, 1.7, 1.8, 1.9 => 2 2.5 => 2
RoundHalfEven RoundingMode = "ROUND_HALF_EVEN"
)
Routine
type Routine struct {
ProjectID string
DatasetID string
RoutineID string
// contains filtered or unexported fields
}
Routine represents a reference to a BigQuery routine. There are multiple types of routines including stored procedures and scalar user-defined functions (UDFs). For more information, see the BigQuery documentation at https://cloud.google.com/bigquery/docs/
func (*Routine) Create
func (r *Routine) Create(ctx context.Context, rm *RoutineMetadata) (err error)
Create creates a Routine in the BigQuery service. Pass in a RoutineMetadata to define the routine.
func (*Routine) Delete
Delete removes a Routine from a dataset.
func (*Routine) FullyQualifiedName
FullyQualifiedName returns an identifer for the routine in project.dataset.routine format.
func (*Routine) Identifier
func (r *Routine) Identifier(f IdentifierFormat) (string, error)
Identifier returns the ID of the routine in the requested format.
For Standard SQL format, the identifier will be quoted if the ProjectID contains dash (-) characters.
func (*Routine) Metadata
func (r *Routine) Metadata(ctx context.Context) (rm *RoutineMetadata, err error)
Metadata fetches the metadata for a given Routine.
func (*Routine) Update
func (r *Routine) Update(ctx context.Context, upd *RoutineMetadataToUpdate, etag string) (rm *RoutineMetadata, err error)
Update modifies properties of a Routine using the API.
RoutineArgument
type RoutineArgument struct {
// The name of this argument. Can be absent for function return argument.
Name string
// Kind indicates the kind of argument represented.
// Possible values:
// ARGUMENT_KIND_UNSPECIFIED
// FIXED_TYPE - The argument is a variable with fully specified
// type, which can be a struct or an array, but not a table.
// ANY_TYPE - The argument is any type, including struct or array,
// but not a table.
Kind string
// Mode is optional, and indicates whether an argument is input or output.
// Mode can only be set for procedures.
//
// Possible values:
// MODE_UNSPECIFIED
// IN - The argument is input-only.
// OUT - The argument is output-only.
// INOUT - The argument is both an input and an output.
Mode string
// DataType provides typing information. Unnecessary for ANY_TYPE Kind
// arguments.
DataType *StandardSQLDataType
}
RoutineArgument represents an argument supplied to a routine such as a UDF or stored procedured.
RoutineDeterminism
type RoutineDeterminism string
RoutineDeterminism specifies the level of determinism that javascript User Defined Functions exhibit.
Deterministic, NotDeterministic
const (
// Deterministic indicates that two calls with the same input to a UDF yield the same output.
Deterministic RoutineDeterminism = "DETERMINISTIC"
// NotDeterministic indicates that the output of the UDF is not guaranteed to yield the same
// output each time for a given set of inputs.
NotDeterministic RoutineDeterminism = "NOT_DETERMINISTIC"
)
RoutineIterator
type RoutineIterator struct {
// contains filtered or unexported fields
}
A RoutineIterator is an iterator over Routines.
func (*RoutineIterator) Next
func (it *RoutineIterator) Next() (*Routine, error)
Next returns the next result. Its second return value is Done if there are no more results. Once Next returns Done, all subsequent calls will return Done.
func (*RoutineIterator) PageInfo
func (it *RoutineIterator) PageInfo() *iterator.PageInfo
PageInfo supports pagination. See the google.golang.org/api/iterator package for details.
RoutineMetadata
type RoutineMetadata struct {
ETag string
// Type indicates the type of routine, such as SCALAR_FUNCTION, PROCEDURE,
// or TABLE_VALUED_FUNCTION.
Type string
CreationTime time.Time
Description string
// DeterminismLevel is only applicable to Javascript UDFs.
DeterminismLevel RoutineDeterminism
LastModifiedTime time.Time
// Language of the routine, such as SQL or JAVASCRIPT.
Language string
// The list of arguments for the the routine.
Arguments []*RoutineArgument
// Information for a remote user-defined function.
RemoteFunctionOptions *RemoteFunctionOptions
ReturnType *StandardSQLDataType
// Set only if the routine type is TABLE_VALUED_FUNCTION.
ReturnTableType *StandardSQLTableType
// For javascript routines, this indicates the paths for imported libraries.
ImportedLibraries []string
// Body contains the routine's body.
// For functions, Body is the expression in the AS clause.
//
// For SQL functions, it is the substring inside the parentheses of a CREATE
// FUNCTION statement.
//
// For JAVASCRIPT function, it is the evaluated string in the AS clause of
// a CREATE FUNCTION statement.
Body string
// For data governance use cases. If set to "DATA_MASKING", the function
// is validated and made available as a masking function. For more information,
// see: https://cloud.google.com/bigquery/docs/user-defined-functions#custom-mask
DataGovernanceType string
}
RoutineMetadata represents details of a given BigQuery Routine.
RoutineMetadataToUpdate
type RoutineMetadataToUpdate struct {
Arguments []*RoutineArgument
Description optional.String
DeterminismLevel optional.String
Type optional.String
Language optional.String
Body optional.String
ImportedLibraries []string
ReturnType *StandardSQLDataType
ReturnTableType *StandardSQLTableType
DataGovernanceType optional.String
}
RoutineMetadataToUpdate governs updating a routine.
RowInsertionError
type RowInsertionError struct {
InsertID string // The InsertID associated with the affected row.
RowIndex int // The 0-based index of the affected row in the batch of rows being inserted.
Errors MultiError
}
RowInsertionError contains all errors that occurred when attempting to insert a row.
func (*RowInsertionError) Error
func (e *RowInsertionError) Error() string
RowIterator
type RowIterator struct {
// StartIndex can be set before the first call to Next. If PageInfo().Token
// is also set, StartIndex is ignored. If Storage API is enabled,
// StartIndex is also ignored because is not supported. IsAccelerated()
// method can be called to check if Storage API is enabled for the RowIterator.
StartIndex uint64
// The schema of the table.
// In some scenarios it will only be available after the first
// call to Next(), like when a call to Query.Read uses
// the jobs.query API for an optimized query path.
Schema Schema
// The total number of rows in the result.
// In some scenarios it will only be available after the first
// call to Next(), like when a call to Query.Read uses
// the jobs.query API for an optimized query path.
// May be zero just after rows were inserted.
TotalRows uint64
// contains filtered or unexported fields
}
A RowIterator provides access to the result of a BigQuery lookup.
func (*RowIterator) ArrowIterator
func (it *RowIterator) ArrowIterator() (ArrowIterator, error)
ArrowIterator gives access to the raw Arrow Record Batch stream to be consumed directly. Experimental: this interface is experimental and may be modified or removed in future versions, regardless of any other documented package stability guarantees. Don't try to mix RowIterator.Next and ArrowIterator.Next calls.
func (*RowIterator) IsAccelerated
func (it *RowIterator) IsAccelerated() bool
IsAccelerated check if the current RowIterator is being accelerated by Storage API.
func (*RowIterator) Next
func (it *RowIterator) Next(dst interface{}) error
Next loads the next row into dst. Its return value is iterator.Done if there are no more results. Once Next returns iterator.Done, all subsequent calls will return iterator.Done.
dst may implement ValueLoader, or may be a *[]Value, *map[string]Value, or struct pointer.
If dst is a *[]Value, it will be set to new []Value whose i'th element will be populated with the i'th column of the row.
If dst is a *map[string]Value, a new map will be created if dst is nil. Then for each schema column name, the map key of that name will be set to the column's value. STRUCT types (RECORD types or nested schemas) become nested maps.
If dst is pointer to a struct, each column in the schema will be matched with an exported field of the struct that has the same name, ignoring case. Unmatched schema columns and struct fields will be ignored.
Each BigQuery column type corresponds to one or more Go types; a matching struct field must be of the correct type. The correspondences are:
STRING string
BOOL bool
INTEGER int, int8, int16, int32, int64, uint8, uint16, uint32
FLOAT float32, float64
BYTES []byte
TIMESTAMP time.Time
DATE civil.Date
TIME civil.Time
DATETIME civil.DateTime
NUMERIC *big.Rat
BIGNUMERIC *big.Rat
The big.Rat type supports numbers of arbitrary size and precision. See https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#numeric-type for more on NUMERIC.
A repeated field corresponds to a slice or array of the element type. BigQuery translates NULL arrays into an empty array, so we follow that behavior. See https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#array_nulls for more about NULL and empty arrays.
A STRUCT type (RECORD or nested schema) corresponds to a nested struct or struct pointer. All calls to Next on the same iterator must use the same struct type.
It is an error to attempt to read a BigQuery NULL value into a struct field, unless the field is of type []byte or is one of the special Null types: NullInt64, NullFloat64, NullBool, NullString, NullTimestamp, NullDate, NullTime or NullDateTime. You can also use a *[]Value or *map[string]Value to read from a table with NULLs.
Examples
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
"google.golang.org/api/iterator"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
q := client.Query("select name, num from t1")
it, err := q.Read(ctx)
if err != nil {
// TODO: Handle error.
}
for {
var row []bigquery.Value
err := it.Next(&row)
if err == iterator.Done {
break
}
if err != nil {
// TODO: Handle error.
}
fmt.Println(row)
}
}
struct
package main
import (
"context"
"fmt"
"cloud.google.com/go/bigquery"
"google.golang.org/api/iterator"
)
func main() {
ctx := context.Background()
client, err := bigquery.NewClient(ctx, "project-id")
if err != nil {
// TODO: Handle error.
}
type score struct {
Name string
Num int
}
q := client.Query("select name, num from t1")
it, err := q.Read(ctx)
if err != nil {
// TODO: Handle error.
}
for {
var s score
err := it.Next(&s)
if err == iterator.Done {
break
}
if err != nil {
// TODO: Handle error.
}
fmt.Println(s)
}
}
func (*RowIterator) PageInfo
func (it *RowIterator) PageInfo() *iterator.PageInfo
PageInfo supports pagination. See the google.golang.org/api/iterator package for details. Currently pagination is not supported when the Storage API is enabled. IsAccelerated() method can be called to check if Storage API is enabled for the RowIterator.
func (*RowIterator) QueryID
func (ri *RowIterator) QueryID() string
QueryID returns a query ID if available, or an empty string.
func (*RowIterator) SourceJob
func (ri *RowIterator) SourceJob() *Job
SourceJob returns an instance of a Job if the RowIterator is backed by a query, or a nil.
Schema
type Schema []*FieldSchema
Schema describes the fields in a table or query result.
func InferSchema
InferSchema tries to derive a BigQuery schema from the supplied struct value. Each exported struct field is mapped to a field in the schema.
The following BigQuery types are inferred from the corresponding Go types. (This is the same mapping as that used for RowIterator.Next.) Fields inferred from these types are marked required (non-nullable).
STRING string
BOOL bool
INTEGER int, int8, int16, int32, int64, uint8, uint16, uint32
FLOAT float32, float64
BYTES []byte
TIMESTAMP time.Time
DATE civil.Date
TIME civil.Time
DATETIME civil.DateTime
NUMERIC *big.Rat
JSON map[string]interface{}
The big.Rat type supports numbers of arbitrary size and precision. Values will be rounded to 9 digits after the decimal point before being transmitted to BigQuery. See https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#numeric-type for more on NUMERIC.
A Go slice or array type is inferred to be a BigQuery repeated field of the element type. The element type must be one of the above listed types.
Due to lack of unique native Go type for GEOGRAPHY, there is no schema inference to GEOGRAPHY at this time.
This package also provides some value types for expressing the corresponding SQL types.
INTERVAL *IntervalValue RANGE *RangeValue
In the case of RANGE types, a RANGE represents a continuous set of values of a given element type (DATE, DATETIME, or TIMESTAMP). InferSchema does not attempt to determine the element type, as it uses generic Value types to denote the start/end of the range.
Nullable fields are inferred from the NullXXX types, declared in this package:
STRING NullString
BOOL NullBool
INTEGER NullInt64
FLOAT NullFloat64
TIMESTAMP NullTimestamp
DATE NullDate
TIME NullTime
DATETIME NullDateTime
GEOGRAPHY NullGeography
For a nullable BYTES field, use the type []byte and tag the field "nullable" (see below). For a nullable NUMERIC field, use the type *big.Rat and tag the field "nullable".
A struct field that is of struct type is inferred to be a required field of type RECORD with a schema inferred recursively. For backwards compatibility, a field of type pointer to struct is also inferred to be required. To get a nullable RECORD field, use the "nullable" tag (see below).
InferSchema returns an error if any of the examined fields is of type uint, uint64, uintptr, map, interface, complex64, complex128, func, or chan. Future versions may handle these cases without error.
Recursively defined structs are also disallowed.
Struct fields may be tagged in a way similar to the encoding/json package. A tag of the form
bigquery:"name"
uses "name" instead of the struct field name as the BigQuery field name. A tag of the form
bigquery:"-"
omits the field from the inferred schema. The "nullable" option marks the field as nullable (not required). It is only needed for []byte, *big.Rat and pointer-to-struct fields, and cannot appear on other fields. In this example, the Go name of the field is retained:
bigquery:",nullable"
Examples
package main
import (
"fmt"
"cloud.google.com/go/bigquery"
)
func main() {
type Item struct {
Name string
Size float64
Count