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Write to MongoDB

When saving RDD data into MongoDB, the data must be convertible to a BSON document. You may need to include a map transformation to convert the data into a Document (or BsonDocument or a DBObject).

The following example creates a 10 document RDD and saves it to the MongoDB collection specified in the SparkConf:

package com.mongodb.spark_examples;
import com.mongodb.spark.MongoSpark;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.sql.SparkSession;
import org.bson.Document;
import static java.util.Arrays.asList;
public final class WriteToMongoDB {
public static void main(final String[] args) throws InterruptedException {
SparkSession spark = SparkSession.builder()
.master("local")
.appName("MongoSparkConnectorIntro")
.config("spark.mongodb.input.uri", "mongodb://127.0.0.1/test.myCollection")
.config("spark.mongodb.output.uri", "mongodb://127.0.0.1/test.myCollection")
.getOrCreate();
JavaSparkContext jsc = new JavaSparkContext(spark.sparkContext());
// Create a RDD of 10 documents
JavaRDD<Document> documents = jsc.parallelize(asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)).map
(new Function<Integer, Document>() {
public Document call(final Integer i) throws Exception {
return Document.parse("{test: " + i + "}");
}
});
/*Start Example: Save data from RDD to MongoDB*****************/
MongoSpark.save(sparkDocuments, writeConfig);
/*End Example**************************************************/
jsc.close();
}
}

MongoSpark.save() can accept a WriteConfig object which specifies various write configuration settings, such as the collection or the write concern.

For example, the following code saves data to the spark collection with a majority write concern:

package com.mongodb.spark_examples;
import com.mongodb.spark.MongoSpark;
import com.mongodb.spark.config.WriteConfig;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.sql.SparkSession;
import org.bson.Document;
import static java.util.Arrays.asList;
import java.util.HashMap;
import java.util.Map;
public final class WriteToMongoDBWriteConfig {
public static void main(final String[] args) throws InterruptedException {
SparkSession spark = SparkSession.builder()
.master("local")
.appName("MongoSparkConnectorIntro")
.config("spark.mongodb.input.uri", "mongodb://127.0.0.1/test.myCollection")
.config("spark.mongodb.output.uri", "mongodb://127.0.0.1/test.myCollection")
.getOrCreate();
JavaSparkContext jsc = new JavaSparkContext(spark.sparkContext());
// Create a custom WriteConfig
Map<String, String> writeOverrides = new HashMap<String, String>();
writeOverrides.put("collection", "spark");
writeOverrides.put("writeConcern.w", "majority");
WriteConfig writeConfig = WriteConfig.create(jsc).withOptions(writeOverrides);
// Create a RDD of 10 documents
JavaRDD<Document> sparkDocuments = jsc.parallelize(asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)).map
(new Function<Integer, Document>() {
public Document call(final Integer i) throws Exception {
return Document.parse("{spark: " + i + "}");
}
});
/*Start Example: Save data from RDD to MongoDB*****************/
MongoSpark.save(sparkDocuments, writeConfig);
/*End Example**************************************************/
jsc.close();
}
}
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