透過「to Neo4j」範本 Google Cloud ，您可以透過 Dataflow 工作將資料集匯入 Neo4j 資料庫，並從 Cloud Storage bucket 中代管的 CSV 檔案取得資料。您也可以在匯入資料的各個步驟中，操控及轉換資料。您可以將範本用於首次匯入和增量匯入。
管道相關規定
- 正在執行的 Neo4j 執行個體
- Cloud Storage bucket
- 要匯入的資料集 (CSV 檔案形式)
- 要使用的工作規格檔案
建立工作規格檔案
工作規格檔案包含 JSON 物件，其中含有下列區段：
config：影響匯入作業方式的全域標記。sources：資料來源定義 (關聯式)。targets：資料目標定義 (圖表：節點/關係)。actions：載入前/後動作。
詳情請參閱 Neo4j 說明文件中的「建立工作規格檔案」。
範本參數
必要參數
- jobSpecUri：工作規格檔案的路徑，內含資料來源、Neo4j 目標和動作的 JSON 說明。
選用參數
- neo4jConnectionUri：Neo4j 連線 JSON 檔案的路徑。
- neo4jConnectionSecretId：Neo4j 連線中繼資料的密鑰 ID。您可以將這個值做為
neo4jConnectionUri的替代值。 - optionsJson：JSON 物件，也稱為執行階段權杖。例如
{token1:value1,token2:value2}. Spec can refer to $token1 and $token2.。預設為空白。 - readQuery：覆寫 SQL 查詢。預設為空白。
- inputFilePattern：文字檔案路徑覆寫，例如
gs://your-bucket/path/*.json。預設為空白。 - disabledAlgorithms：以半形逗號分隔要停用的演算法。如果此值設為
none，則不會停用任何演算法。請謹慎使用這個參數，因為預設停用的演算法可能存在安全漏洞或效能問題。例如：SSLv3, RC4。 - extraFilesToStage：以半形逗號分隔的 Cloud Storage 路徑或 Secret Manager 密鑰，用於在工作站中暫存檔案。這些檔案會儲存在每個工作站的 /extra_files 目錄中。例如：
gs://<BUCKET_NAME>/file.txt,projects/<PROJECT_ID>/secrets/<SECRET_ID>/versions/<VERSION_ID>。
執行範本
控制台
- 前往 Dataflow 的「Create job from template」(透過範本建立工作) 頁面。 前往「依據範本建立工作」
- 在「工作名稱」欄位中，輸入專屬工作名稱。
- 選用：如要使用區域端點，請從下拉式選單中選取值。預設區域為
us-central1。如需可執行 Dataflow 工作的地區清單，請參閱「Dataflow 位置」。
- 從「Dataflow template」(Dataflow 範本) 下拉式選單中選取 the Google Cloud to Neo4j template。
- 在提供的參數欄位中輸入參數值。
- 按一下「Run Job」(執行工作)。
gcloud
在殼層或終端機中執行範本：
gcloud dataflow flex-template run JOB_NAME \ --template-file-gcs-location=gs://dataflow-templates-REGION_NAME/VERSION/flex/Google_Cloud_to_Neo4j \ --project=PROJECT_ID \ --region=REGION_NAME \ --parameters \ jobSpecUri=JOB_SPEC_URI,\ neo4jConnectionUri=NEO4J_CONNECTION_URI,\
更改下列內容：
JOB_NAME： 您選擇的不重複工作名稱VERSION： 您要使用的範本版本您可以使用下列值：
latest，使用範本的最新版本，該版本位於值區中非依日期命名的上層資料夾：gs://dataflow-templates-REGION_NAME/latest/- 版本名稱 (例如
2023-09-12-00_RC00)，用於指定範本版本，該版本會以巢狀結構存放在值區中依日期命名的上層資料夾中：gs://dataflow-templates-REGION_NAME/
REGION_NAME： 您要部署 Dataflow 工作的地區，例如us-central1JOB_SPEC_URI：工作規格檔案的路徑NEO4J_CONNECTION_URI：Neo4j 連線中繼資料的路徑
API
如要使用 REST API 執行範本，請傳送 HTTP POST 要求。如要進一步瞭解 API 和授權範圍，請參閱 projects.templates.launch。
POST https://dataflow.googleapis.com/v1b3/projects/PROJECT_ID/locations/LOCATION/flexTemplates:launch { "launchParameter": { "jobName": "JOB_NAME", "parameters": { "jobSpecUri": "JOB_SPEC_URI", "neo4jConnectionUri": "NEO4J_CONNECTION_URI", }, "containerSpecGcsPath": "gs://dataflow-templates-LOCATION/VERSION/flex/Google_Cloud_to_Neo4j", "environment": { "maxWorkers": "10" } } }
更改下列內容：
PROJECT_ID： 您要執行 Dataflow 工作的專案 ID Google CloudJOB_NAME： 您選擇的不重複工作名稱VERSION： 您要使用的範本版本您可以使用下列值：
latest，使用範本的最新版本，該版本位於值區中非依日期命名的上層資料夾：gs://dataflow-templates-REGION_NAME/latest/- 版本名稱 (例如
2023-09-12-00_RC00)，用於指定範本版本，該版本會以巢狀結構存放在值區中依日期命名的上層資料夾中：gs://dataflow-templates-REGION_NAME/
LOCATION： 您要部署 Dataflow 工作的地區，例如us-central1JOB_SPEC_URI：工作規格檔案的路徑NEO4J_CONNECTION_URI：Neo4j 連線中繼資料的路徑
範本原始碼
Java
/*
* Copyright (C) 2021 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not
* use this file except in compliance with the License. You may obtain a copy of
* the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations under
* the License.
*/
package com.google.cloud.teleport.v2.neo4j.templates;
import static java.util.stream.Collectors.groupingBy;
import static java.util.stream.Collectors.mapping;
import static java.util.stream.Collectors.toList;
import com.google.cloud.teleport.metadata.Template;
import com.google.cloud.teleport.metadata.Template.AdditionalDocumentationBlock;
import com.google.cloud.teleport.metadata.TemplateCategory;
import com.google.cloud.teleport.v2.common.UncaughtExceptionLogger;
import com.google.cloud.teleport.v2.neo4j.actions.ActionDoFnFactory;
import com.google.cloud.teleport.v2.neo4j.actions.ActionPreloadFactory;
import com.google.cloud.teleport.v2.neo4j.actions.preload.PreloadAction;
import com.google.cloud.teleport.v2.neo4j.database.Neo4jConnection;
import com.google.cloud.teleport.v2.neo4j.model.InputValidator;
import com.google.cloud.teleport.v2.neo4j.model.Json;
import com.google.cloud.teleport.v2.neo4j.model.Json.ParsingResult;
import com.google.cloud.teleport.v2.neo4j.model.connection.ConnectionParams;
import com.google.cloud.teleport.v2.neo4j.model.enums.ArtifactType;
import com.google.cloud.teleport.v2.neo4j.model.helpers.JobSpecMapper;
import com.google.cloud.teleport.v2.neo4j.model.helpers.OptionsParamsMapper;
import com.google.cloud.teleport.v2.neo4j.model.helpers.TargetQuerySpec;
import com.google.cloud.teleport.v2.neo4j.model.helpers.TargetQuerySpec.TargetQuerySpecBuilder;
import com.google.cloud.teleport.v2.neo4j.model.helpers.TargetSequence;
import com.google.cloud.teleport.v2.neo4j.model.job.ActionContext;
import com.google.cloud.teleport.v2.neo4j.model.job.OptionsParams;
import com.google.cloud.teleport.v2.neo4j.options.Neo4jFlexTemplateOptions;
import com.google.cloud.teleport.v2.neo4j.providers.Provider;
import com.google.cloud.teleport.v2.neo4j.providers.ProviderFactory;
import com.google.cloud.teleport.v2.neo4j.transforms.Neo4jRowWriterTransform;
import com.google.cloud.teleport.v2.neo4j.utils.BeamBlock;
import com.google.cloud.teleport.v2.neo4j.utils.FileSystemUtils;
import com.google.cloud.teleport.v2.neo4j.utils.ModelUtils;
import com.google.cloud.teleport.v2.neo4j.utils.ProcessingCoder;
import com.google.cloud.teleport.v2.utils.SecretManagerUtils;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.LinkedHashSet;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Set;
import java.util.stream.Collectors;
import java.util.stream.Stream;
import org.apache.beam.runners.dataflow.options.DataflowPipelineOptions;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.coders.VarIntCoder;
import org.apache.beam.sdk.io.FileSystems;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.schemas.Schema;
import org.apache.beam.sdk.transforms.Create;
import org.apache.beam.sdk.transforms.ParDo;
import org.apache.beam.sdk.transforms.Wait;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.Row;
import org.apache.beam.sdk.values.TypeDescriptor;
import org.apache.commons.lang3.StringUtils;
import org.jetbrains.annotations.NotNull;
import org.neo4j.importer.v1.Configuration;
import org.neo4j.importer.v1.ImportSpecification;
import org.neo4j.importer.v1.actions.Action;
import org.neo4j.importer.v1.actions.ActionStage;
import org.neo4j.importer.v1.sources.Source;
import org.neo4j.importer.v1.targets.CustomQueryTarget;
import org.neo4j.importer.v1.targets.NodeTarget;
import org.neo4j.importer.v1.targets.RelationshipTarget;
import org.neo4j.importer.v1.targets.Target;
import org.neo4j.importer.v1.targets.TargetType;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* Dataflow template which reads Google Cloud data (Text, BigQuery) and writes it to Neo4j.
*
* <p>In case of BigQuery, the source data can be either a table or a SQL query.
*
* <p>Check out <a
* href="https://github.com/GoogleCloudPlatform/DataflowTemplates/blob/main/v2/googlecloud-to-neo4j/README_Google_Cloud_to_Neo4j.md">README</a>
* for instructions on how to use or modify this template.
*/
@Template(
name = "Google_Cloud_to_Neo4j",
category = TemplateCategory.BATCH,
displayName = "Google Cloud to Neo4j",
description =
"The Google Cloud to Neo4j template lets you import a dataset into a Neo4j database through a Dataflow job, "
+ "sourcing data from CSV files hosted in Google Cloud Storage buckets. It also lets you to manipulate and transform the data "
+ "at various steps of the import. You can use the template for both first-time imports and incremental imports.",
optionsClass = Neo4jFlexTemplateOptions.class,
flexContainerName = "googlecloud-to-neo4j",
contactInformation = "https://support.neo4j.com/",
documentation =
"https://cloud.google.com/dataflow/docs/guides/templates/provided/google-cloud-to-neo4j",
requirements = {
"A running Neo4j instance",
"A Google Cloud Storage bucket",
"A dataset to import, in the form of CSV files",
"A job specification file to use"
},
additionalDocumentation = {
@AdditionalDocumentationBlock(
name = "Create a job specification file",
content = {
"The job specification file consists of a JSON object with the following sections:\n"
+ "- `config` - global flags affecting how the import is performed.\n"
+ "- `sources` - data source definitions (relational).\n"
+ "- `targets` - data target definitions (graph: nodes/relationships/custom queries).\n"
+ "- `actions` - pre/post-load actions.\n"
+ "For more information, see <a href=\"https://neo4j.com/docs/dataflow-google-cloud/job-specification/\" class=\"external\">Create a job specification file</a> in the Neo4j documentation."
})
},
preview = true)
public class GoogleCloudToNeo4j {
private static final Logger LOG = LoggerFactory.getLogger(GoogleCloudToNeo4j.class);
private final OptionsParams optionsParams;
private final ConnectionParams neo4jConnection;
private final ImportSpecification importSpecification;
private final Configuration globalSettings;
private final Pipeline pipeline;
private final String templateVersion;
private final TargetSequence targetSequence = new TargetSequence();
/**
* Main class for template. Initializes job using run-time on pipelineOptions.
*
* @param pipelineOptions framework supplied arguments
*/
public GoogleCloudToNeo4j(Neo4jFlexTemplateOptions pipelineOptions) {
////////////////////////////
// Job name gets a date on it when running within the container, but not with DirectRunner
// final String jobName = pipelineOptions.getJobName() + "-" + System.currentTimeMillis();
// pipelineOptions.setJobName(jobName);
// Set pipeline options
this.pipeline = Pipeline.create(pipelineOptions);
FileSystems.setDefaultPipelineOptions(pipelineOptions);
this.optionsParams = OptionsParamsMapper.fromPipelineOptions(pipelineOptions);
// Validate pipeline
processValidations(
"Errors found validating pipeline options: ",
InputValidator.validateNeo4jPipelineOptions(pipelineOptions));
this.templateVersion = readTemplateVersion(pipelineOptions);
String neo4jConnectionJson = readConnectionSettings(pipelineOptions);
ParsingResult parsingResult = InputValidator.validateNeo4jConnection(neo4jConnectionJson);
if (!parsingResult.isSuccessful()) {
processValidations(
"Errors found validating Neo4j connection: ",
parsingResult.formatErrors("Could not validate connection JSON"));
}
this.neo4jConnection = Json.map(parsingResult, ConnectionParams.class);
this.importSpecification = JobSpecMapper.parse(pipelineOptions.getJobSpecUri(), optionsParams);
globalSettings = importSpecification.getConfiguration();
///////////////////////////////////
// Source specific validations
for (Source source : importSpecification.getSources()) {
// get provider implementation for source
Provider providerImpl = ProviderFactory.of(source, targetSequence);
providerImpl.configure(optionsParams);
}
}
private static String readTemplateVersion(Neo4jFlexTemplateOptions options) {
Map<String, String> labels = options.as(DataflowPipelineOptions.class).getLabels();
String defaultVersion = "UNKNOWN";
if (labels == null) {
return defaultVersion;
}
return labels.getOrDefault("goog-dataflow-provided-template-version", defaultVersion);
}
private static String readConnectionSettings(Neo4jFlexTemplateOptions options) {
String secretId = options.getNeo4jConnectionSecretId();
if (StringUtils.isNotEmpty(secretId)) {
return SecretManagerUtils.getSecret(secretId);
}
String uri = options.getNeo4jConnectionUri();
try {
return FileSystemUtils.getPathContents(uri);
} catch (Exception e) {
throw new RuntimeException(
String.format("Unable to read Neo4j configuration at URI %s: ", uri), e);
}
}
/**
* Runs a pipeline which reads data from various sources and writes it to Neo4j.
*
* @param args arguments to the pipeline
*/
public static void main(String[] args) {
UncaughtExceptionLogger.register();
Neo4jFlexTemplateOptions options =
PipelineOptionsFactory.fromArgs(args).withValidation().as(Neo4jFlexTemplateOptions.class);
// Allow users to supply their own list of disabled algorithms if necessary
if (StringUtils.isBlank(options.getDisabledAlgorithms())) {
options.setDisabledAlgorithms(
"SSLv3, RC4, DES, MD5withRSA, DH keySize < 1024, EC keySize < 224, 3DES_EDE_CBC, anon,"
+ " NULL");
}
LOG.info("Job: {}", options.getJobSpecUri());
GoogleCloudToNeo4j template = new GoogleCloudToNeo4j(options);
template.run();
}
/** Raises RuntimeExceptions for validation errors. */
private void processValidations(String description, List<String> validationMessages) {
StringBuilder sb = new StringBuilder();
if (!validationMessages.isEmpty()) {
for (String msg : validationMessages) {
sb.append(msg);
sb.append(System.lineSeparator());
}
throw new RuntimeException(description + " " + sb);
}
}
public void run() {
try (Neo4jConnection directConnect =
new Neo4jConnection(this.neo4jConnection, this.templateVersion)) {
boolean resetDb = globalSettings.get(Boolean.class, "reset_db").orElse(false);
if (!resetDb) {
directConnect.verifyConnectivity();
} else {
directConnect.resetDatabase();
}
}
////////////////////////////
// If an action transformation has no upstream PCollection, it will use this default context
PCollection<Row> defaultActionContext =
pipeline.apply(
"Default Context",
Create.empty(TypeDescriptor.of(Row.class)).withCoder(ProcessingCoder.of()));
var processingQueue = new BeamBlock(defaultActionContext);
runPreloadActions(findActionsByStage(ActionStage.START).collect(toList()));
Map<ActionStage, List<PCollection<?>>> preActionRows =
findActionsByStages(
Set.of(
ActionStage.PRE_NODES, ActionStage.PRE_RELATIONSHIPS, ActionStage.PRE_QUERIES))
.map(action -> Map.entry(action.getStage(), runAction(action, defaultActionContext)))
.collect(
groupingBy(
Entry::getKey, mapping(Entry::getValue, Collectors.<PCollection<?>>toList())));
var sourceRows = new ArrayList<PCollection<?>>(importSpecification.getSources().size());
var targetRows = new HashMap<TargetType, List<PCollection<?>>>(targetCount());
var allActiveTargets =
importSpecification.getTargets().getAll().stream()
.filter(Target::isActive)
.collect(toList());
var allActiveNodeTargets =
importSpecification.getTargets().getNodes().stream()
.filter(Target::isActive)
.collect(toList());
////////////////////////////
// Process sources
for (var source : importSpecification.getSources()) {
String sourceName = source.getName();
var activeSourceTargets =
allActiveTargets.stream()
.filter(target -> target.getSource().equals(sourceName))
.collect(toList());
if (activeSourceTargets.isEmpty()) {
return;
}
// get provider implementation for source
Provider provider = ProviderFactory.of(source, targetSequence);
provider.configure(optionsParams);
PCollection<Row> sourceMetadata =
pipeline.apply(
String.format("Metadata for source %s", sourceName), provider.queryMetadata());
sourceRows.add(sourceMetadata);
Schema sourceBeamSchema = sourceMetadata.getSchema();
processingQueue.addToQueue(ArtifactType.source, sourceName, defaultActionContext);
////////////////////////////
// Optimization: if some of the current source's targets either
// - do not alter the source query (i.e. define no transformations)
// - or the source provider does not support SQL pushdown
// then the source PCollection can be defined here and reused across all the relevant targets
PCollection<Row> nullableSourceBeamRows = null;
if (!provider.supportsSqlPushDown()
|| activeSourceTargets.stream()
.anyMatch(target -> !ModelUtils.targetHasTransforms(target))) {
nullableSourceBeamRows =
pipeline
.apply("Query " + sourceName, provider.querySourceBeamRows(sourceBeamSchema))
.setRowSchema(sourceBeamSchema);
}
List<NodeTarget> nodeTargets = getTargetsByType(activeSourceTargets, TargetType.NODE);
for (NodeTarget target : nodeTargets) {
TargetQuerySpec targetQuerySpec =
new TargetQuerySpecBuilder()
.sourceBeamSchema(sourceBeamSchema)
.nullableSourceRows(nullableSourceBeamRows)
.target(target)
.build();
String nodeStepDescription =
targetSequence.getSequenceNumber(target)
+ ": "
+ sourceName
+ "->"
+ target.getName()
+ " nodes";
PCollection<Row> preInsertBeamRows =
pipeline.apply(
"Query " + nodeStepDescription, provider.queryTargetBeamRows(targetQuerySpec));
List<PCollection<?>> dependencies =
new ArrayList<>(preActionRows.getOrDefault(ActionStage.PRE_NODES, List.of()));
dependencies.add(
processingQueue.resolveOutputs(target.getDependencies(), nodeStepDescription));
PCollection<Row> blockingReturn =
preInsertBeamRows
.apply(
"** Unblocking "
+ nodeStepDescription
+ "(after "
+ String.join(", ", target.getDependencies())
+ " and pre-nodes actions)",
Wait.on(dependencies))
.setCoder(preInsertBeamRows.getCoder())
.apply(
"Writing " + nodeStepDescription,
new Neo4jRowWriterTransform(
importSpecification,
neo4jConnection,
templateVersion,
targetSequence,
target))
.setCoder(preInsertBeamRows.getCoder());
targetRows
.computeIfAbsent(TargetType.NODE, (type) -> new ArrayList<>(nodeTargets.size()))
.add(blockingReturn);
processingQueue.addToQueue(ArtifactType.node, target.getName(), blockingReturn);
}
////////////////////////////
// Write relationship targets
List<RelationshipTarget> relationshipTargets =
getTargetsByType(activeSourceTargets, TargetType.RELATIONSHIP);
for (var target : relationshipTargets) {
var targetQuerySpec =
new TargetQuerySpecBuilder()
.nullableSourceRows(nullableSourceBeamRows)
.sourceBeamSchema(sourceBeamSchema)
.target(target)
.startNodeTarget(
findNodeTargetByName(allActiveNodeTargets, target.getStartNodeReference()))
.endNodeTarget(
findNodeTargetByName(allActiveNodeTargets, target.getEndNodeReference()))
.build();
String relationshipStepDescription =
targetSequence.getSequenceNumber(target)
+ ": "
+ sourceName
+ "->"
+ target.getName()
+ " edges";
PCollection<Row> preInsertBeamRows;
if (ModelUtils.targetHasTransforms(target)) {
preInsertBeamRows =
pipeline.apply(
"Query " + relationshipStepDescription,
provider.queryTargetBeamRows(targetQuerySpec));
} else {
preInsertBeamRows = nullableSourceBeamRows;
}
List<PCollection<?>> dependencies =
new ArrayList<>(preActionRows.getOrDefault(ActionStage.PRE_RELATIONSHIPS, List.of()));
Set<String> dependencyNames = new LinkedHashSet<>(target.getDependencies());
dependencyNames.add(target.getStartNodeReference());
dependencyNames.add(target.getEndNodeReference());
dependencies.add(
processingQueue.resolveOutputs(dependencyNames, relationshipStepDescription));
PCollection<Row> blockingReturn =
preInsertBeamRows
.apply(
"** Unblocking "
+ relationshipStepDescription
+ "(after "
+ String.join(", ", dependencyNames)
+ " and pre-relationships actions)",
Wait.on(dependencies))
.setCoder(preInsertBeamRows.getCoder())
.apply(
"Writing " + relationshipStepDescription,
new Neo4jRowWriterTransform(
importSpecification,
neo4jConnection,
templateVersion,
targetSequence,
target))
.setCoder(preInsertBeamRows.getCoder());
targetRows
.computeIfAbsent(
TargetType.RELATIONSHIP, (type) -> new ArrayList<>(relationshipTargets.size()))
.add(blockingReturn);
// serialize relationships
processingQueue.addToQueue(ArtifactType.edge, target.getName(), blockingReturn);
}
////////////////////////////
// Custom query targets
List<CustomQueryTarget> customQueryTargets =
getTargetsByType(activeSourceTargets, TargetType.QUERY);
for (Target target : customQueryTargets) {
String customQueryStepDescription =
targetSequence.getSequenceNumber(target)
+ ": "
+ sourceName
+ "->"
+ target.getName()
+ " (custom query)";
List<PCollection<?>> dependencies =
new ArrayList<>(preActionRows.getOrDefault(ActionStage.PRE_QUERIES, List.of()));
dependencies.add(
processingQueue.resolveOutputs(target.getDependencies(), customQueryStepDescription));
// note: nullableSourceBeamRows is guaranteed to be non-null here since custom query targets
// cannot define source transformations
PCollection<Row> blockingReturn =
nullableSourceBeamRows
.apply(
"** Unblocking "
+ customQueryStepDescription
+ "(after "
+ String.join(", ", target.getDependencies())
+ ")",
Wait.on(dependencies))
.setCoder(nullableSourceBeamRows.getCoder())
.apply(
"Writing " + customQueryStepDescription,
new Neo4jRowWriterTransform(
importSpecification,
neo4jConnection,
templateVersion,
targetSequence,
target))
.setCoder(nullableSourceBeamRows.getCoder());
targetRows
.computeIfAbsent(TargetType.QUERY, (type) -> new ArrayList<>(customQueryTargets.size()))
.add(blockingReturn);
processingQueue.addToQueue(ArtifactType.custom_query, target.getName(), blockingReturn);
}
}
// Process POST-* actions, gather outputs and run END actions
List<PCollection<?>> endActionDependencies =
findActionsByStage(ActionStage.POST_SOURCES)
.map(action -> runAction(action, defaultActionContext, sourceRows))
.collect(Collectors.toCollection(ArrayList::new));
endActionDependencies.addAll(
findActionsByStage(ActionStage.POST_NODES)
.map(
action ->
runAction(
action,
defaultActionContext,
targetRows.getOrDefault(TargetType.NODE, List.of())))
.collect(toList()));
endActionDependencies.addAll(
findActionsByStage(ActionStage.POST_RELATIONSHIPS)
.map(
action ->
runAction(
action,
defaultActionContext,
targetRows.getOrDefault(TargetType.RELATIONSHIP, List.of())))
.collect(toList()));
endActionDependencies.addAll(
findActionsByStage(ActionStage.POST_QUERIES)
.map(
action ->
runAction(
action,
defaultActionContext,
targetRows.getOrDefault(TargetType.QUERY, List.of())))
.collect(toList()));
findActionsByStage(ActionStage.END)
.map(action -> runAction(action, defaultActionContext, endActionDependencies))
.forEach(GoogleCloudToNeo4j::noOp);
// For a Dataflow Flex Template, do NOT waitUntilFinish().
pipeline.run();
}
private PCollection<Row> runAction(Action action, PCollection<Row> defaultActionContext) {
return runAction(action, defaultActionContext, List.of());
}
private PCollection<Row> runAction(
Action action, PCollection<Row> defaultActionContext, List<PCollection<?>> dependencies) {
var actionName = action.getName();
return pipeline
.apply(String.format("** Setup %s", actionName), Create.of(1))
.apply(
String.format("** Wait on %s dependencies", action.getStage()), Wait.on(dependencies))
.setCoder(VarIntCoder.of())
.apply(
String.format("Running action %s", actionName),
ParDo.of(ActionDoFnFactory.of(newActionContext(action))))
.setCoder(defaultActionContext.getCoder());
}
private Stream<Action> findActionsByStage(ActionStage stage) {
return findActionsByStages(Set.of(stage));
}
private Stream<Action> findActionsByStages(Set<ActionStage> stages) {
return importSpecification.getActions().stream()
.filter(action -> stages.contains(action.getStage()));
}
private void runPreloadActions(List<Action> actions) {
for (Action action : actions) {
LOG.debug("Executing START action: {}", action.getName());
// Get targeted execution context
ActionContext context = new ActionContext(action, neo4jConnection, templateVersion);
PreloadAction actionImpl = ActionPreloadFactory.of(action, context);
List<String> msgs = actionImpl.execute();
for (String msg : msgs) {
LOG.info("START action {} output: {}", action.getName(), msg);
}
}
}
@NotNull
private ActionContext newActionContext(Action action) {
return new ActionContext(action, this.neo4jConnection, this.templateVersion);
}
private static NodeTarget findNodeTargetByName(List<NodeTarget> nodes, String reference) {
return nodes.stream()
.filter(target -> reference.equals(target.getName()))
.findFirst()
.orElseThrow(
() -> new IllegalArgumentException("Could not find active node target: " + reference));
}
@SuppressWarnings("unchecked")
private <T extends Target> List<T> getTargetsByType(
List<Target> activeSourceTargets, TargetType targetType) {
return activeSourceTargets.stream()
.filter(target -> target.getTargetType() == targetType)
.map(target -> (T) target)
.collect(toList());
}
private static <T> void noOp(T item) {}
private int targetCount() {
var targets = this.importSpecification.getTargets();
return targets.getNodes().size()
+ targets.getRelationships().size()
+ targets.getCustomQueries().size();
}
}
後續步驟
- 瞭解 Dataflow 範本。
- 請參閱 Google 提供的範本清單。