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JavaShakespeare.java
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JavaShakespeare.java
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/*
* Copyright 2018 Google Inc. All Rights Reserved.
*
* 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.spark.bigquery.examples;
import java.io.PrintStream;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
public class JavaShakespeare {
public static void main(String[] args) {
SparkSession spark = SparkSession.builder().appName("spark-bigquery-demo").getOrCreate();
String outputBigqueryTable = "wordcount_dataset.wordcount_output";
if (args.length == 1) {
outputBigqueryTable = args[0];
} else if (args.length > 1) {
usage();
}
// Use the Cloud Storage bucket for temporary BigQuery export data used
// by the connector. This assumes the Cloud Storage connector for
// Hadoop is configured.
String bucket = spark.sparkContext().hadoopConfiguration().get("fs.gs.system.bucket");
spark.conf().set("temporaryGcsBucket", bucket);
// Load data in from BigQuery.
Dataset<Row> wordsDF =
spark
.read()
.format("bigquery")
.option("table", "bigquery-public-data.samples.shakespeare")
.load()
.cache();
wordsDF.show();
wordsDF.printSchema();
wordsDF.createOrReplaceTempView("words");
// Perform word count.
Dataset<Row> wordCountDF =
spark.sql("SELECT word, SUM(word_count) AS word_count FROM words GROUP BY word");
wordCountDF.show();
wordCountDF.printSchema();
// Saving the data to BigQuery
wordCountDF.write().format("bigquery").option("table", outputBigqueryTable).save();
}
private static void usage() {
PrintStream out = System.out;
out.println("usage: spark [OUTPUT_BIGQUERY_TABLE]");
out.println("[OUTPUT_BIGQUERY_TABLE] Set the output bigquery table to ");
out.println(" OUTPUT_BIGQUERY_TABLE. By default the location");
out.println(" is wordcount_dataset.wordcount_output");
System.exit(1);
}
}