I am using Spark 1.3 and would like to join on multiple columns using python interface (SparkSQL)
The following works:
I first register them as temp tables.
numeric.registerTempTable("numeric")
Ref.registerTempTable("Ref")
test = numeric.join(Ref, numeric.ID == Ref.ID, joinType='inner')
I would now like to join them based on multiple columns.
I get SyntaxError
: invalid syntax with this:
test = numeric.join(Ref,
numeric.ID == Ref.ID AND numeric.TYPE == Ref.TYPE AND
numeric.STATUS == Ref.STATUS , joinType='inner')
You should use &
/ |
operators and be careful about operator precedence (==
has lower precedence than bitwise AND
and 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|
## +---+---+---+---+---+---+