Spark: Joining with array

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I need to join a dataframe with a string column to one with array of string so that if one of the values in the array is matched, the rows will join.

I tried this but I guess it's not support. Any other way to do this?

import org.apache.spark.SparkConf
import org.apache.spark.sql.SparkSession

val sparkConf = new SparkConf().setMaster("local[*]").setAppName("test")
val spark = SparkSession.builder().config(sparkConf).getOrCreate()

import spark.implicits._

val left = spark.sparkContext.parallelize(Seq(1, 2, 3)).toDF("col1")
val right = spark.sparkContext.parallelize(Seq((Array(1, 2), "Yes"),(Array(3),"No"))).toDF("col1", "col2")

left.join(right,"col1")

Throws:

org.apache.spark.sql.AnalysisException: cannot resolve '(col1 =col1)' due to data type mismatch: differing types in '(col1 =

col1)' (int and array).;;

apache-spark-sql apache-spark scala
3 Answers

The most succinct way to do this is to use the array_contains spark sql expression as shown below, that said I've compared the performance of this with the performance of doing an explode and join as shown in a previous answer and the explode seems more performant.

import org.apache.spark.sql.functions.expr
import spark.implicits._

val left = Seq(1, 2, 3).toDF("col1")

val right = Seq((Array(1, 2), "Yes"),(Array(3),"No")).toDF("col1", "col2").withColumnRenamed("col1", "col1_array")

val joined = left.join(right, expr("array_contains(col1_array, col1)")).show

+----+----------+----+
|col1|col1_array|col2|
+----+----------+----+
|   1|    [1, 2]| Yes|
|   2|    [1, 2]| Yes|
|   3|       [3]|  No|
+----+----------+----+

Note you can't use the org.apache.spark.sql.functions.array_contains function directly as it requires the second argument to be a literal as opposed to a column expression.

user_29944270
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