Cloud Storage Text to Datastore 模板[已弃用]

此模板已弃用，将于 2023 年第三季度移除。请迁移到 Cloud Storage Text to Firestore 模板。

Cloud Storage Text to Datastore 模板是一种批处理流水线，可从存储在 Cloud Storage 中的文本文件读取数据，并将采用 JSON 编码的实体写入 Datastore。输入文本文件中的所有行都必须采用 指定的 JSON 格式。

流水线要求

  • 必须在目标项目中启用 Datastore。

模板参数

必需参数

  • textReadPattern：指定文本数据文件位置的 Cloud Storage 路径模式。例如 gs://mybucket/somepath/*.json。
  • datastoreWriteProjectId：要将 Datastore 实体写入到的 Google Cloud 项目的 ID。
  • errorWritePath：要用于写入在处理期间发生的故障的错误日志输出文件。例如 gs://your-bucket/errors/。

可选参数

  • javascriptTextTransformGcsPath：.js 文件的 Cloud Storage URI，用于定义要使用的 JavaScript 用户定义的函数 (UDF)。例如 gs://my-bucket/my-udfs/my_file.js。
  • javascriptTextTransformFunctionName：要使用的 JavaScript 用户定义的函数 (UDF) 的名称。例如，如果 JavaScript 函数代码为 myTransform(inJson) { /*...do stuff...*/ }，则函数名称为 myTransform。如需查看 JavaScript UDF 示例，请参阅 UDF 示例 (https://github.com/GoogleCloudPlatform/DataflowTemplates#udf-examples)。
  • datastoreHintNumWorkers：Datastore 逐步增加限制步骤中的预期工作器数量的提示。默认值为 500。

运行模板

控制台gcloudAPI
  1. 转到 Dataflow 基于模板创建作业页面。
    2. 转到“基于模板创建作业”
  2. 在作业名称字段中，输入唯一的作业名称。
  3. 可选：对于区域性端点，从下拉菜单中选择一个值。默认区域为 us-central1。

    如需查看可以在其中运行 Dataflow 作业的区域列表，请参阅 Dataflow 位置。

  4. 从 Dataflow 模板下拉菜单中，选择 the Text Files on Cloud Storage to Datastore template。
  5. 在提供的参数字段中，输入您的参数值。
  6. 点击运行作业。

在 shell 或终端中，运行模板：

gcloud dataflow jobs run JOB_NAME \
    --gcs-location gs://dataflow-templates-REGION_NAME/VERSION/GCS_Text_to_Datastore \
    --region REGION_NAME \
    --parameters \
textReadPattern=PATH_TO_INPUT_TEXT_FILES,\
javascriptTextTransformGcsPath=PATH_TO_JAVASCRIPT_UDF_FILE,\
javascriptTextTransformFunctionName=JAVASCRIPT_FUNCTION,\
datastoreWriteProjectId=PROJECT_ID,\
errorWritePath=ERROR_FILE_WRITE_PATH

替换以下内容：

  • JOB_NAME：您选择的唯一性作业名称
  • VERSION：您要使用的模板的版本

    您可使用以下值：

  • REGION_NAME：要在其中部署 Dataflow 作业的区域，例如 us-central1
  • PATH_TO_INPUT_TEXT_FILES：Cloud Storage 上的输入文件模式
  • JAVASCRIPT_FUNCTION： 您要使用的 JavaScript 用户定义的函数 (UDF) 的名称

    例如，如果您的 JavaScript 函数代码为 myTransform(inJson) { /*...do stuff...*/ }，则函数名称为 myTransform。如需查看 JavaScript UDF 示例，请参阅 UDF 示例。

  • PATH_TO_JAVASCRIPT_UDF_FILE： .js 文件的 Cloud Storage URI，用于定义您要使用的 JavaScript 用户定义的函数 (UDF)，例如 gs://my-bucket/my-udfs/my_file.js
  • ERROR_FILE_WRITE_PATH：Cloud Storage 上错误文件所需的路径

如需使用 REST API 来运行模板，请发送 HTTP POST 请求。如需详细了解 API 及其授权范围，请参阅 projects.templates.launch。

POST https://dataflow.googleapis.com/v1b3/projects/PROJECT_ID/locations/LOCATION/templates:launch?gcsPath=gs://dataflow-templates-LOCATION/VERSION/GCS_Text_to_Datastore
{
   "jobName": "JOB_NAME",
   "parameters": {
       "textReadPattern": "PATH_TO_INPUT_TEXT_FILES",
       "javascriptTextTransformGcsPath": "PATH_TO_JAVASCRIPT_UDF_FILE",
       "javascriptTextTransformFunctionName": "JAVASCRIPT_FUNCTION",
       "datastoreWriteProjectId": "PROJECT_ID",
       "errorWritePath": "ERROR_FILE_WRITE_PATH"
   },
   "environment": { "zone": "us-central1-f" }
}

替换以下内容：

  • PROJECT_ID：您要在其中运行 Dataflow 作业的 Google Cloud 项目 ID
  • JOB_NAME：您选择的唯一性作业名称
  • VERSION：您要使用的模板的版本

    您可使用以下值：

  • LOCATION：要在其中部署 Dataflow 作业的区域，例如 us-central1
  • PATH_TO_INPUT_TEXT_FILES：Cloud Storage 上的输入文件模式
  • JAVASCRIPT_FUNCTION： 您要使用的 JavaScript 用户定义的函数 (UDF) 的名称

    例如，如果您的 JavaScript 函数代码为 myTransform(inJson) { /*...do stuff...*/ }，则函数名称为 myTransform。如需查看 JavaScript UDF 示例，请参阅 UDF 示例。

  • PATH_TO_JAVASCRIPT_UDF_FILE： .js 文件的 Cloud Storage URI，用于定义您要使用的 JavaScript 用户定义的函数 (UDF)，例如 gs://my-bucket/my-udfs/my_file.js
  • ERROR_FILE_WRITE_PATH：Cloud Storage 上错误文件所需的路径
Java
/*
 * Copyright (C) 2018 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.templates;

import com.google.cloud.teleport.metadata.MultiTemplate;
import com.google.cloud.teleport.metadata.Template;
import com.google.cloud.teleport.metadata.TemplateCategory;
import com.google.cloud.teleport.templates.TextToDatastore.TextToDatastoreOptions;
import com.google.cloud.teleport.templates.common.DatastoreConverters.DatastoreWriteOptions;
import com.google.cloud.teleport.templates.common.DatastoreConverters.WriteJsonEntities;
import com.google.cloud.teleport.templates.common.ErrorConverters.ErrorWriteOptions;
import com.google.cloud.teleport.templates.common.ErrorConverters.LogErrors;
import com.google.cloud.teleport.templates.common.FirestoreNestedValueProvider;
import com.google.cloud.teleport.templates.common.JavascriptTextTransformer.JavascriptTextTransformerOptions;
import com.google.cloud.teleport.templates.common.JavascriptTextTransformer.TransformTextViaJavascript;
import com.google.cloud.teleport.templates.common.TextConverters.FilesystemReadOptions;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.io.TextIO;
import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.options.ValueProvider;
import org.apache.beam.sdk.values.TupleTag;

/**
 * Dataflow template which reads from a Text Source and writes JSON encoded Entities into Datastore.
 * The JSON is expected to be in the format of: <a
 * href="https://cloud.google.com/datastore/docs/reference/rest/v1/Entity">Entity</a>
 *
 * <p>Check out <a
 * href="https://github.com/GoogleCloudPlatform/DataflowTemplates/blob/main/v1/README_GCS_Text_to_Datastore.md">README
 * Datastore</a> or <a
 * href="https://github.com/GoogleCloudPlatform/DataflowTemplates/blob/main/v1/README_GCS_Text_to_Firestore.md">README
 * Firestore</a> for instructions on how to use or modify this template.
 */
@MultiTemplate({
  @Template(
      name = "GCS_Text_to_Datastore",
      category = TemplateCategory.LEGACY,
      displayName = "Text Files on Cloud Storage to Datastore [Deprecated]",
      description =
          "The Cloud Storage Text to Datastore template is a batch pipeline that reads from text files stored in "
              + "Cloud Storage and writes JSON encoded Entities to Datastore. "
              + "Each line in the input text files must be in the <a href=\"https://cloud.google.com/datastore/docs/reference/rest/v1/Entity\">specified JSON format</a>.",
      optionsClass = TextToDatastoreOptions.class,
      skipOptions = {
        "firestoreWriteProjectId",
        "firestoreWriteEntityKind",
        "firestoreWriteNamespace",
        "firestoreHintNumWorkers",
        "javascriptTextTransformReloadIntervalMinutes",
        // This template doesn't use neither firestoreWriteEntityKind/Namespace
        // nor datastoreWriteEntityKind/Namespace pipeline options.
        "datastoreWriteEntityKind",
        "datastoreWriteNamespace"
      },
      documentation =
          "https://cloud.google.com/dataflow/docs/guides/templates/provided/cloud-storage-to-datastore",
      contactInformation = "https://cloud.google.com/support",
      preview = true,
      requirements = {"Datastore must be enabled in the destination project."}),
  @Template(
      name = "GCS_Text_to_Firestore",
      category = TemplateCategory.BATCH,
      displayName = "Text Files on Cloud Storage to Firestore (Datastore mode)",
      description =
          "The Cloud Storage Text to Firestore template is a batch pipeline that reads from text files stored in "
              + "Cloud Storage and writes JSON encoded Entities to Firestore. "
              + "Each line in the input text files must be in the <a href=\"https://cloud.google.com/datastore/docs/reference/rest/v1/Entity\">specified JSON format</a>.",
      optionsClass = TextToDatastoreOptions.class,
      skipOptions = {
        "datastoreWriteProjectId",
        "datastoreWriteEntityKind",
        "datastoreWriteNamespace",
        "datastoreHintNumWorkers",
        "javascriptTextTransformReloadIntervalMinutes",
        // This template doesn't use neither firestoreWriteEntityKind/Namespace
        // nor datastoreWriteEntityKind/Namespace pipeline options.
        "firestoreWriteEntityKind",
        "firestoreWriteNamespace"
      },
      documentation =
          "https://cloud.google.com/dataflow/docs/guides/templates/provided/cloud-storage-to-firestore",
      contactInformation = "https://cloud.google.com/support",
      requirements = {"Firestore must be enabled in the destination project."})
})
public class TextToDatastore {

  public static <T> ValueProvider<T> selectProvidedInput(
      ValueProvider<T> datastoreInput, ValueProvider<T> firestoreInput) {
    return new FirestoreNestedValueProvider(datastoreInput, firestoreInput);
  }

  /** TextToDatastore Pipeline Options. */
  public interface TextToDatastoreOptions
      extends PipelineOptions,
          FilesystemReadOptions,
          JavascriptTextTransformerOptions,
          DatastoreWriteOptions,
          ErrorWriteOptions {}

  /**
   * Runs a pipeline which reads from a Text Source, passes the Text to a Javascript UDF, writes the
   * JSON encoded Entities to a TextIO sink.
   *
   * <p>If your Text Source does not contain JSON encoded Entities, then you'll need to supply a
   * Javascript UDF which transforms your data to be JSON encoded Entities.
   *
   * @param args arguments to the pipeline
   */
  public static void main(String[] args) {
    TextToDatastoreOptions options =
        PipelineOptionsFactory.fromArgs(args).withValidation().as(TextToDatastoreOptions.class);

    TupleTag<String> errorTag = new TupleTag<String>("errors") {};

    Pipeline pipeline = Pipeline.create(options);

    pipeline
        .apply(TextIO.read().from(options.getTextReadPattern()))
        .apply(
            TransformTextViaJavascript.newBuilder()
                .setFileSystemPath(options.getJavascriptTextTransformGcsPath())
                .setFunctionName(options.getJavascriptTextTransformFunctionName())
                .build())
        .apply(
            WriteJsonEntities.newBuilder()
                .setProjectId(
                    selectProvidedInput(
                        options.getDatastoreWriteProjectId(), options.getFirestoreWriteProjectId()))
                .setHintNumWorkers(
                    selectProvidedInput(
                        options.getDatastoreHintNumWorkers(), options.getFirestoreHintNumWorkers()))
                .setErrorTag(errorTag)
                .build())
        .apply(
            LogErrors.newBuilder()
                .setErrorWritePath(options.getErrorWritePath())
                .setErrorTag(errorTag)
                .build());

    pipeline.run();
  }
}

后续步骤