Java Code Examples for org.apache.spark.api.java.JavaRDD#zipWithUniqueId()

The following examples show how to use org.apache.spark.api.java.JavaRDD#zipWithUniqueId() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source File: SparkStorageUtils.java    From DataVec with Apache License 2.0 5 votes vote down vote up
/**
 * Save a {@code JavaRDD<List<List<Writable>>>} to a Hadoop {@link org.apache.hadoop.io.SequenceFile}. Each record
 * is given a unique (but noncontiguous) {@link LongWritable} key, and values are stored as {@link SequenceRecordWritable} instances.
 * <p>
 * Use {@link #restoreSequenceFileSequences(String, JavaSparkContext)} to restore values saved with this method.
 *
 * @param path           Path to save the sequence file
 * @param rdd            RDD to save
 * @param maxOutputFiles Nullable. If non-null: first coalesce the RDD to the specified size (number of partitions)
 *                       to limit the maximum number of output sequence files
 * @see #saveSequenceFile(String, JavaRDD)
 * @see #saveMapFileSequences(String, JavaRDD)
 */
public static void saveSequenceFileSequences(String path, JavaRDD<List<List<Writable>>> rdd,
                 Integer maxOutputFiles) {
    path = FilenameUtils.normalize(path, true);
    if (maxOutputFiles != null) {
        rdd = rdd.coalesce(maxOutputFiles);
    }
    JavaPairRDD<List<List<Writable>>, Long> dataIndexPairs = rdd.zipWithUniqueId(); //Note: Long values are unique + NOT contiguous; more efficient than zipWithIndex
    JavaPairRDD<LongWritable, SequenceRecordWritable> keyedByIndex =
                    dataIndexPairs.mapToPair(new SequenceRecordSavePrepPairFunction());

    keyedByIndex.saveAsNewAPIHadoopFile(path, LongWritable.class, SequenceRecordWritable.class,
                    SequenceFileOutputFormat.class);
}
 
Example 2
Source File: SparkStorageUtils.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up
/**
 * Save a {@code JavaRDD<List<List<Writable>>>} to a Hadoop {@link org.apache.hadoop.io.SequenceFile}. Each record
 * is given a unique (but noncontiguous) {@link LongWritable} key, and values are stored as {@link SequenceRecordWritable} instances.
 * <p>
 * Use {@link #restoreSequenceFileSequences(String, JavaSparkContext)} to restore values saved with this method.
 *
 * @param path           Path to save the sequence file
 * @param rdd            RDD to save
 * @param maxOutputFiles Nullable. If non-null: first coalesce the RDD to the specified size (number of partitions)
 *                       to limit the maximum number of output sequence files
 * @see #saveSequenceFile(String, JavaRDD)
 * @see #saveMapFileSequences(String, JavaRDD)
 */
public static void saveSequenceFileSequences(String path, JavaRDD<List<List<Writable>>> rdd,
                 Integer maxOutputFiles) {
    path = FilenameUtils.normalize(path, true);
    if (maxOutputFiles != null) {
        rdd = rdd.coalesce(maxOutputFiles);
    }
    JavaPairRDD<List<List<Writable>>, Long> dataIndexPairs = rdd.zipWithUniqueId(); //Note: Long values are unique + NOT contiguous; more efficient than zipWithIndex
    JavaPairRDD<LongWritable, SequenceRecordWritable> keyedByIndex =
                    dataIndexPairs.mapToPair(new SequenceRecordSavePrepPairFunction());

    keyedByIndex.saveAsNewAPIHadoopFile(path, LongWritable.class, SequenceRecordWritable.class,
                    SequenceFileOutputFormat.class);
}
 
Example 3
Source File: SparkStorageUtils.java    From DataVec with Apache License 2.0 3 votes vote down vote up
/**
 * Save a {@code JavaRDD<List<Writable>>} to a Hadoop {@link org.apache.hadoop.io.SequenceFile}. Each record is given
 * a unique (but noncontiguous) {@link LongWritable} key, and values are stored as {@link RecordWritable} instances.
 * <p>
 * Use {@link #restoreSequenceFile(String, JavaSparkContext)} to restore values saved with this method.
 *
 * @param path           Path to save the sequence file
 * @param rdd            RDD to save
 * @param maxOutputFiles Nullable. If non-null: first coalesce the RDD to the specified size (number of partitions)
 *                       to limit the maximum number of output sequence files
 * @see #saveSequenceFileSequences(String, JavaRDD)
 * @see #saveMapFile(String, JavaRDD)
 */
public static void saveSequenceFile(String path, JavaRDD<List<Writable>> rdd,  Integer maxOutputFiles) {
    path = FilenameUtils.normalize(path, true);
    if (maxOutputFiles != null) {
        rdd = rdd.coalesce(maxOutputFiles);
    }
    JavaPairRDD<List<Writable>, Long> dataIndexPairs = rdd.zipWithUniqueId(); //Note: Long values are unique + NOT contiguous; more efficient than zipWithIndex
    JavaPairRDD<LongWritable, RecordWritable> keyedByIndex =
                    dataIndexPairs.mapToPair(new RecordSavePrepPairFunction());

    keyedByIndex.saveAsNewAPIHadoopFile(path, LongWritable.class, RecordWritable.class,
                    SequenceFileOutputFormat.class);
}
 
Example 4
Source File: SparkStorageUtils.java    From deeplearning4j with Apache License 2.0 3 votes vote down vote up
/**
 * Save a {@code JavaRDD<List<Writable>>} to a Hadoop {@link org.apache.hadoop.io.SequenceFile}. Each record is given
 * a unique (but noncontiguous) {@link LongWritable} key, and values are stored as {@link RecordWritable} instances.
 * <p>
 * Use {@link #restoreSequenceFile(String, JavaSparkContext)} to restore values saved with this method.
 *
 * @param path           Path to save the sequence file
 * @param rdd            RDD to save
 * @param maxOutputFiles Nullable. If non-null: first coalesce the RDD to the specified size (number of partitions)
 *                       to limit the maximum number of output sequence files
 * @see #saveSequenceFileSequences(String, JavaRDD)
 * @see #saveMapFile(String, JavaRDD)
 */
public static void saveSequenceFile(String path, JavaRDD<List<Writable>> rdd,  Integer maxOutputFiles) {
    path = FilenameUtils.normalize(path, true);
    if (maxOutputFiles != null) {
        rdd = rdd.coalesce(maxOutputFiles);
    }
    JavaPairRDD<List<Writable>, Long> dataIndexPairs = rdd.zipWithUniqueId(); //Note: Long values are unique + NOT contiguous; more efficient than zipWithIndex
    JavaPairRDD<LongWritable, RecordWritable> keyedByIndex =
                    dataIndexPairs.mapToPair(new RecordSavePrepPairFunction());

    keyedByIndex.saveAsNewAPIHadoopFile(path, LongWritable.class, RecordWritable.class,
                    SequenceFileOutputFormat.class);
}