pyspark.RDD.leftOuterJoin¶
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RDD.leftOuterJoin(other: pyspark.rdd.RDD[Tuple[K, U]], numPartitions: Optional[int] = None) → pyspark.rdd.RDD[Tuple[K, Tuple[V, Optional[U]]]]¶ Perform a left outer join of self and other.
For each element (k, v) in self, the resulting RDD will either contain all pairs (k, (v, w)) for w in other, or the pair (k, (v, None)) if no elements in other have key k.
Hash-partitions the resulting RDD into the given number of partitions.
Examples
>>> x = sc.parallelize([("a", 1), ("b", 4)]) >>> y = sc.parallelize([("a", 2)]) >>> sorted(x.leftOuterJoin(y).collect()) [('a', (1, 2)), ('b', (4, None))]