如何在udf中使用广播收藏集? [英] How to use a broadcast collection in a udf?
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问题描述
如何在Spark SQL 1.6.1 udf中使用广播集合.应当从Main SQL中调用Udf,如下所示
How to use a broadcast collection in Spark SQL 1.6.1 udf. Udf should be called from Main SQL as shown below
sqlContext.sql("""Select col1,col2,udf_1(key) as value_from_udf FROM table_a""")
udf_1()
应该查看广播的小集合,以将值返回给主sql.
udf_1()
should be looking through a broadcast small collection to return value to main sql.
推荐答案
下面是pySpark
中的一个最小可重现的示例,它说明了使用广播变量执行查找的过程,其中将lambda
函数用作UDF
SQL
语句.
Here's a minimal reproducible example in pySpark
, illustrating the use of broadcast variables to perform lookups, employing a lambda
function as an UDF
inside a SQL
statement.
# 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|
+---+---+----+
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