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/* | |
* Copyright (C) 2015 Google Inc. | |
* | |
* 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.dataflow.examples.complete; | |
import com.google.api.services.bigquery.model.TableFieldSchema; | |
import com.google.api.services.bigquery.model.TableRow; | |
import com.google.api.services.bigquery.model.TableSchema; | |
import com.google.cloud.dataflow.examples.common.DataflowExampleUtils; | |
import com.google.cloud.dataflow.examples.common.ExampleBigQueryTableOptions; | |
import com.google.cloud.dataflow.examples.common.ExamplePubsubTopicOptions; | |
import com.google.cloud.dataflow.sdk.Pipeline; | |
import com.google.cloud.dataflow.sdk.PipelineResult; | |
import com.google.cloud.dataflow.sdk.coders.TableRowJsonCoder; | |
import com.google.cloud.dataflow.sdk.io.BigQueryIO; | |
import com.google.cloud.dataflow.sdk.io.PubsubIO; | |
import com.google.cloud.dataflow.sdk.options.Default; | |
import com.google.cloud.dataflow.sdk.options.Description; | |
import com.google.cloud.dataflow.sdk.options.PipelineOptionsFactory; | |
import com.google.cloud.dataflow.sdk.runners.DataflowPipelineRunner; | |
import com.google.cloud.dataflow.sdk.transforms.DoFn; | |
import com.google.cloud.dataflow.sdk.transforms.ParDo; | |
import java.io.IOException; | |
import java.util.ArrayList; | |
/** | |
* A streaming Dataflow Example using BigQuery output. | |
* | |
* <p>This pipeline example reads lines of text from a PubSub topic, splits each line | |
* into individual words, capitalizes those words, and writes the output to | |
* a BigQuery table. | |
* | |
* <p>By default, the example will run a separate pipeline to inject the data from the default | |
* {@literal --inputFile} to the Pub/Sub {@literal --pubsubTopic}. It will make it available for | |
* the streaming pipeline to process. You may override the default {@literal --inputFile} with the | |
* file of your choosing. You may also set {@literal --inputFile} to an empty string, which will | |
* disable the automatic Pub/Sub injection, and allow you to use separate tool to control the input | |
* to this example. | |
* | |
* <p>The example is configured to use the default Pub/Sub topic and the default BigQuery table | |
* from the example common package (there are no defaults for a general Dataflow pipeline). | |
* You can override them by using the {@literal --pubsubTopic}, {@literal --bigQueryDataset}, and | |
* {@literal --bigQueryTable} options. If the Pub/Sub topic or the BigQuery table do not exist, | |
* the example will try to create them. | |
* | |
* <p>The example will try to cancel the pipelines on the signal to terminate the process (CTRL-C) | |
* and then exits. | |
*/ | |
public class StreamingLogExtract { | |
private static final String PUBSUB_TIMESTAMP_LABEL_KEY = "publishTime"; | |
/** A DoFn that tokenizes lines of text into individual words. */ | |
static class ExtractWords extends DoFn<String, String> { | |
@Override | |
public void processElement(ProcessContext c) { | |
String[] words = c.element().split("[^a-zA-Z']+"); | |
for (String word : words) { | |
if (!word.isEmpty()) { | |
c.output(word); | |
} | |
} | |
} | |
} | |
/** A DoFn that uppercases a word. */ | |
static class Uppercase extends DoFn<String, String> { | |
@Override | |
public void processElement(ProcessContext c) { | |
c.output(c.element().toUpperCase()); | |
} | |
} | |
/** | |
* Converts strings into BigQuery rows. | |
*/ | |
static class ExtractPayload extends DoFn<TableRow, TableRow> { | |
/** | |
* In this example, put only the Payload into single BigQuery field. | |
*/ | |
@Override | |
public void processElement(ProcessContext c) { | |
c.output(new TableRow().set("textPayload", c.element().get("textPayload"))); | |
} | |
static TableSchema getSchema() { | |
return new TableSchema().setFields(new ArrayList<TableFieldSchema>() { | |
// Compose the list of TableFieldSchema from tableSchema. | |
{ | |
add(new TableFieldSchema().setName("textPayload").setType("STRING")); | |
} | |
}); | |
} | |
} | |
private interface StreamingLogExtractOptions | |
extends ExamplePubsubTopicOptions, ExampleBigQueryTableOptions { | |
@Description("Input file to inject to Pub/Sub topic") | |
@Default.String("gs://dataflow-samples/shakespeare/kinglear.txt") | |
String getInputFile(); | |
void setInputFile(String value); | |
} | |
/** | |
* Sets up and starts streaming pipeline. | |
* | |
* @throws IOException if there is a problem setting up resources | |
*/ | |
public static void main(String[] args) throws IOException { | |
StreamingLogExtractOptions options = PipelineOptionsFactory.fromArgs(args) | |
.withValidation() | |
.as(StreamingLogExtractOptions.class); | |
options.setStreaming(true); | |
// In order to cancel the pipelines automatically, | |
// {@literal DataflowPipelineRunner} is forced to be used. | |
options.setRunner(DataflowPipelineRunner.class); | |
options.setBigQuerySchema(ExtractPayload.getSchema()); | |
DataflowExampleUtils dataflowUtils = new DataflowExampleUtils(options); | |
dataflowUtils.setup(); | |
Pipeline pipeline = Pipeline.create(options); | |
String tableSpec = new StringBuilder() | |
.append(options.getProject()).append(":") | |
.append(options.getBigQueryDataset()).append(".") | |
.append(options.getBigQueryTable()) | |
.toString(); | |
pipeline | |
.apply(PubsubIO.Read | |
.topic(options.getPubsubTopic()) | |
.withCoder(TableRowJsonCoder.of()) | |
.timestampLabel(PUBSUB_TIMESTAMP_LABEL_KEY)) | |
.apply(ParDo.of(new ExtractPayload())) | |
.apply(BigQueryIO.Write.to(tableSpec) | |
.withSchema(ExtractPayload.getSchema())); | |
PipelineResult result = pipeline.run(); | |
// dataflowUtils will try to cancel the pipeline and the injector before the program exists. | |
dataflowUtils.waitToFinish(result); | |
} | |
} |
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