Left Anti joins Spark?

Question

I defined two tables:

 val tableName = "table1"
    val tableName2 = "table2"

    val format = new SimpleDateFormat("yyyy-MM-dd")
      val data = List(
        List("mike", 26, true),
        List("susan", 26, false),
        List("john", 33, true)
      )
    val data2 = List(
        List("mike", "grade1", 45, "baseball", new java.sql.Date(format.parse("1957-12-10").getTime)),
        List("john", "grade2", 33, "soccer", new java.sql.Date(format.parse("1978-06-07").getTime)),
        List("john", "grade2", 32, "golf", new java.sql.Date(format.parse("1978-06-07").getTime)),
        List("mike", "grade2", 26, "basketball", new java.sql.Date(format.parse("1978-06-07").getTime)),
        List("lena", "grade2", 23, "baseball", new java.sql.Date(format.parse("1978-06-07").getTime))
      )

      val rdd = sparkContext.parallelize(data).map(Row.fromSeq(_))
      val rdd2 = sparkContext.parallelize(data2).map(Row.fromSeq(_))
      val schema = StructType(Array(
        StructField("name", StringType, true),
        StructField("age", IntegerType, true),
        StructField("isBoy", BooleanType, false)
      ))
    val schema2 = StructType(Array(
        StructField("name", StringType, true),
        StructField("grade", StringType, true),
        StructField("howold", IntegerType, true),
        StructField("hobby", StringType, true),
        StructField("birthday", DateType, false)
      ))

      val df = sqlContext.createDataFrame(rdd, schema)
      val df2 = sqlContext.createDataFrame(rdd2, schema2)
      df.createOrReplaceTempView(tableName)
      df2.createOrReplaceTempView(tableName2)

I am trying to build a query to return rows from table1 that does not have the corresponding row in table2. I tried to do this using this query:

Select * from table1 LEFT JOIN table2 ON table1.name = table2.name AND table1.age = table2.howold AND table2.name IS NULL AND table2.howold IS NULL

but it just gives me all the rows from table1:

List ({"name": "John", "age": 33, "isBoy": true}, {"Name": "Susan", "age": 26, "isBoy" false}, {"Name": "Mike", "age": 26, "isBoy": true})

How to make this type of connection in Spark effective?

SQL-, , , , . , ..

Answer 1

"left anti" - API DataFrame, SQL (API DataFrame , SQL, ):

API DataFrame:

df.as("table1").join(
  df2.as("table2"),
  $"table1.name" === $"table2.name" && $"table1.age" === $"table2.howold",
  "leftanti"
)

SQL:

sqlContext.sql(
  """SELECT table1.* FROM table1
    | LEFT ANTI JOIN table2
    | ON table1.name = table2.name AND table1.age = table2.howold
  """.stripMargin)

: , , toDF, "", - , :

val df = List(
  ("mike", 26, true),
  ("susan", 26, false),
  ("john", 33, true)
).toDF("name", "age", "isBoy")

val df2 = List(
  ("mike", "grade1", 45, "baseball", new java.sql.Date(format.parse("1957-12-10").getTime)),
  ("john", "grade2", 33, "soccer", new java.sql.Date(format.parse("1978-06-07").getTime)),
  ("john", "grade2", 32, "golf", new java.sql.Date(format.parse("1978-06-07").getTime)),
  ("mike", "grade2", 26, "basketball", new java.sql.Date(format.parse("1978-06-07").getTime)),
  ("lena", "grade2", 23, "baseball", new java.sql.Date(format.parse("1978-06-07").getTime))
).toDF("name", "grade", "howold", "hobby", "birthday").withColumn("birthday", $"birthday".cast(DateType))

Answer 2

except ( , , c/p :()

val a = sc.parallelize(Seq((1,"a",123),(2,"b",456))).toDF("col1","col2","col3")
val b= sc.parallelize(Seq((4,"a",432),(2,"t",431),(2,"b",456))).toDF("col1","col2","col3")

scala> a.show()
+----+----+----+
|col1|col2|col3|
+----+----+----+
|   1|   a| 123|
|   2|   b| 456|
+----+----+----+


scala> b.show()
+----+----+----+
|col1|col2|col3|
+----+----+----+
|   4|   a| 432|
|   2|   t| 431|
|   2|   b| 456|
+----+----+----+

scala> a.except(b).show()
+----+----+----+
|col1|col2|col3|
+----+----+----+
|   1|   a| 123|
+----+----+----+

Answer 3

SQL ( , SPARK)

Select * from table1 LEFT JOIN table2 ON table1.name = table2.name AND table1.age = table2.howold where table2.name IS NULL 

1,

Answer 4

You can use the left anti.

dfRcc20.as("a").join(dfClientesDuplicados.as("b")
  ,col("a.eteerccdiid")===col("b.eteerccdiid")&&
    col("a.eteerccdinr")===col("b.eteerccdinr")
  ,"left_anti")