Reputation: 505
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()
should be looking through a broadcast small collection to return value to main sql.
Upvotes: 12
Views: 11285
Reputation: 24178
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|
+---+---+----+
Upvotes: 15