如何在Pyspark中加入多个列？

Question

我正在使用Spark 1.3,并希望使用python接口(SparkSQL)加入多个列

以下作品:

我首先将它们注册为临时表.

numeric.registerTempTable("numeric")
Ref.registerTempTable("Ref")

test  = numeric.join(Ref, numeric.ID == Ref.ID, joinType='inner')

我现在想基于多个列加入它们.

我得到SyntaxError:语法无效:

test  = numeric.join(Ref,
   numeric.ID == Ref.ID AND numeric.TYPE == Ref.TYPE AND
   numeric.STATUS == Ref.STATUS ,  joinType='inner')

Answer 1

您应该使用&/ |运算符并注意运算符优先级(==优先级低于按位AND和OR):

df1 = sqlContext.createDataFrame(
    [(1, "a", 2.0), (2, "b", 3.0), (3, "c", 3.0)],
    ("x1", "x2", "x3"))

df2 = sqlContext.createDataFrame(
    [(1, "f", -1.0), (2, "b", 0.0)], ("x1", "x2", "x3"))

df = df1.join(df2, (df1.x1 == df2.x1) & (df1.x2 == df2.x2))
df.show()

## +---+---+---+---+---+---+
## | x1| x2| x3| x1| x2| x3|
## +---+---+---+---+---+---+
## |  2|  b|3.0|  2|  b|0.0|
## +---+---+---+---+---+---+

Answer 2

另一种方法是:

df1 = sqlContext.createDataFrame(
    [(1, "a", 2.0), (2, "b", 3.0), (3, "c", 3.0)],
    ("x1", "x2", "x3"))

df2 = sqlContext.createDataFrame(
    [(1, "f", -1.0), (2, "b", 0.0)], ("x1", "x2", "x4"))

df = df1.join(df2, ['x1','x2'])
df.show()

哪个输出:

+---+---+---+---+
| x1| x2| x3| x4|
+---+---+---+---+
|  2|  b|3.0|0.0|
+---+---+---+---+

主要优点是表连接的列不会在输出中重复,从而降低遇到错误的风险,例如:org.apache.spark.sql.AnalysisException: Reference 'x1' is ambiguous, could be: x1#50L, x1#57L.

每当两个表中的列具有不同的名称,(让我们在上面的例子说,df2有列y1,y2和y4),可以使用下面的语法:

df = df1.join(df2.withColumnRenamed('y1','x1').withColumnRenamed('y2','x2'), ['x1','x2'])

Answer 3

test = numeric.join(Ref, 
   on=[
     numeric.ID == Ref.ID, 
     numeric.TYPE == Ref.TYPE,
     numeric.STATUS == Ref.STATUS 
   ], how='inner')