如何在udf中使用广播集合？

Question

如何在Spark SQL 1.6.1 udf中使用广播集合.应该从Main SQL调用Udf,如下所示

sqlContext.sql("""Select col1,col2,udf_1(key) as value_from_udf FROM table_a""")

udf_1() 应该通过广播小集合查找返回值到主sql.

Answer 1

这是一个可重复性最小的示例pySpark,说明使用广播变量执行查找,将lambda函数用作语句UDF内部SQL.

# Create dummy data and register as table
df = sc.parallelize([
    (1,"a"),
    (2,"b"),
    (3,"c")]).toDF(["num","let"])
df.registerTempTable('table')

# Create broadcast variable from local dictionary
myDict = {1: "y", 2: "x", 3: "z"}
broadcastVar = sc.broadcast(myDict) 
# Alternatively, if your dict is a key-value rdd, 
# you can do sc.broadcast(rddDict.collectAsMap())

# Create lookup function and apply it
sqlContext.registerFunction("lookup", lambda x: broadcastVar.value.get(x))
sqlContext.sql('select num, let, lookup(num) as test from table').show()
+---+---+----+
|num|let|test|
+---+---+----+
|  1|  a|   y|
|  2|  b|   x|
|  3|  c|   z|
+---+---+----+