maropu commented on a change in pull request #28087: [SPARK-31319][SQL][DOCS] Document UDFs/UDAFs in SQL Reference URL: https://github.com/apache/spark/pull/28087#discussion_r406649416
########## File path: examples/src/main/scala/org/apache/spark/examples/sql/UserDefinedScalar.scala ########## @@ -0,0 +1,81 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.spark.examples.sql + +// $example on:udf_scalar$ +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.functions.udf +// $example off:udf_scalar$ + +object UserDefinedScalar { + + def main(args: Array[String]): Unit = { + // $example on:udf_scalar$ + val spark = SparkSession + .builder() + .appName("Spark SQL UDF scalar example") + .getOrCreate() + + // Define and register a zero-argument non-deterministic UDF + // UDF is deterministic by default, i.e. produces the same result for the same input. + val random = udf(() => Math.random()) + spark.udf.register("random", random.asNondeterministic()) + spark.sql("SELECT random()").show() + // +-------+ + // |UDF() | + // +-------+ + // |xxxxxxx| + // +-------+ + + // Define and register a one-argument UDF + val plusOne = udf((x: Int) => x + 1) + spark.udf.register("plusOne", plusOne) + spark.sql("SELECT plusOne(5)").show() + // +------+ + // |UDF(5)| + // +------+ + // | 6| + // +------+ + + // Define a two-argument UDF and register it with Spark in one step + spark.udf.register("strLenScala", (_: String).length + (_: Int)) + spark.sql("SELECT strLenScala('test', 1)").show() + // +--------------------+ + // |strLenScala(test, 1)| + // +--------------------+ + // | 5| + // +--------------------+ + + // UDF in a WHERE clause + spark.udf.register("oneArgFilter", (n: Int) => { n > 5 }) + spark.range(1, 10).createOrReplaceTempView("test") + spark.sql("SELECT * FROM test WHERE oneArgFilter(id)").show() + // +---+ + // | id| + // +---+ + // | 6| + // | 7| + // | 8| + // | 9| + // +---+ + + // $example off:udf_scalar$ + + spark.stop() + } + Review comment: nit: remove the blank line. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
