kotlin-spark-api_3.2.0_2.13/org.jetbrains.kotlinx.spark.api/leftOuterJoin

leftOuterJoin

fun <K, V, W> JavaRDD<Tuple2<K, V>>.leftOuterJoin(other: JavaRDD<Tuple2<K, W>>, partitioner: Partitioner): JavaRDD<Tuple2<K, Tuple2<V, Optional<W>>>>

Perform a left outer join of this and other. For each element (k, v) in this, the resulting RDD will either contain all pairs (k, (v, Some(w))) for w in other, or the pair (k, (v, None)) if no elements in other have key k. Uses the given Partitioner to partition the output RDD.

fun <K, V, W> JavaRDD<Tuple2<K, V>>.leftOuterJoin(other: JavaRDD<Tuple2<K, W>>): JavaRDD<Tuple2<K, Tuple2<V, Optional<W>>>>

Perform a left outer join of this and other. For each element (k, v) in this, the resulting RDD will either contain all pairs (k, (v, Some(w))) for w in other, or the pair (k, (v, None)) if no elements in other have key k. Hash-partitions the output using the existing partitioner/parallelism level.

fun <K, V, W> JavaRDD<Tuple2<K, V>>.leftOuterJoin(other: JavaRDD<Tuple2<K, W>>, numPartitions: Int): JavaRDD<Tuple2<K, Tuple2<V, Optional<W>>>>

Perform a left outer join of this and other. For each element (k, v) in this, the resulting RDD will either contain all pairs (k, (v, Some(w))) for w in other, or the pair (k, (v, None)) if no elements in other have key k. Hash-partitions the output into numPartitions partitions.

fun <K, V, W> JavaDStream<Tuple2<K, V>>.leftOuterJoin(other: JavaDStream<Tuple2<K, W>>, numPartitions: Int = dstream().ssc().sc().defaultParallelism()): JavaDStream<Tuple2<K, Tuple2<V, Optional<W>>>>

Return a new DStream by applying 'left outer join' between RDDs of this DStream and other DStream. Hash partitioning is used to generate the RDDs with numPartitions partitions.

fun <K, V, W> JavaDStream<Tuple2<K, V>>.leftOuterJoin(other: JavaDStream<Tuple2<K, W>>, partitioner: Partitioner): JavaDStream<Tuple2<K, Tuple2<V, Optional<W>>>>

Return a new DStream by applying 'left outer join' between RDDs of this DStream and other DStream. The supplied org.apache.spark.Partitioner is used to control the partitioning of each RDD.