/** * Groups items with the same key, assuming the items with the same key are next to each other in the * collection. It does not perform shuffle, therefore it is much faster than using much more * universal Spark RDD `groupByKey`. For this method to be useful with Cassandra tables, the key must * represent a prefix of the primary key, containing at least the partition key of the Cassandra * table. */ public JavaPairRDD<K, Collection<V>> spanByKey() { return new PairRDDJavaFunctions<>(rdd()).spanByKey(kClassTag()); }
/** * Groups items with the same key, assuming the items with the same key are next to each other in the * collection. It does not perform shuffle, therefore it is much faster than using much more * universal Spark RDD `groupByKey`. For this method to be useful with Cassandra tables, the key must * represent a prefix of the primary key, containing at least the partition key of the Cassandra * table. */ public JavaPairRDD<K, Collection<V>> spanByKey() { return new PairRDDJavaFunctions<>(rdd()).spanByKey(kClassTag()); }
/** * Groups items with the same key, assuming the items with the same key are next to each other in the * collection. It does not perform shuffle, therefore it is much faster than using much more * universal Spark RDD `groupByKey`. For this method to be useful with Cassandra tables, the key must * represent a prefix of the primary key, containing at least the partition key of the Cassandra * table. */ public JavaPairRDD<K, Collection<V>> spanByKey() { return new PairRDDJavaFunctions<>(rdd()).spanByKey(kClassTag()); }
/** * Groups items with the same key, assuming the items with the same key are next to each other in the * collection. It does not perform shuffle, therefore it is much faster than using much more * universal Spark RDD `groupByKey`. For this method to be useful with Cassandra tables, the key must * represent a prefix of the primary key, containing at least the partition key of the Cassandra * table. */ public JavaPairRDD<K, Collection<V>> spanByKey() { return new PairRDDJavaFunctions<>(rdd()).spanByKey(kClassTag()); }
/** * Groups items with the same key, assuming the items with the same key are next to each other in the * collection. It does not perform shuffle, therefore it is much faster than using much more * universal Spark RDD `groupByKey`. For this method to be useful with Cassandra tables, the key must * represent a prefix of the primary key, containing at least the partition key of the Cassandra * table. */ public JavaPairRDD<K, Collection<V>> spanByKey() { return new PairRDDJavaFunctions<>(rdd()).spanByKey(kClassTag()); }