Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/7176#discussion_r33833159
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala ---
@@ -0,0 +1,95 @@
+/*
+ * 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.sql
+
+import java.sql.Timestamp
+
+import org.apache.spark.sql.types._
+import org.scalacheck.{Arbitrary, Gen}
+
+/**
+ * Random data generators for Spark SQL DataTypes. These generators do not
generate uniformly random
+ * values; instead, they're biased to return "interesting" values (such as
maximum / minimum values)
+ * with higher probability.
+ */
+object RandomDataGenerator {
+
+ /**
+ * Returns a function which generates random values for the given
[[DataType]], or `None` if no
+ * random data generator is defined for that data type. The generated
values will use an external
+ * representation of the data type; for example, the random generator
for [[DateType]] will return
+ * instances of [[java.sql.Date]] and the generator for [[StructType]]
will return a
+ * [[org.apache.spark.Row]].
+ *
+ * @param dataType the type to generate values for
+ * @param nullable whether null values should be generated
+ * @return a ScalaCheck [[Gen]] which can be used to produce random
values.
+ */
+ def forType(
+ dataType: DataType,
+ nullable: Boolean = true): Option[Gen[Any]] = {
+ val valueGenerator: Option[Gen[Any]] = dataType match {
+ case StringType => Some(Arbitrary.arbitrary[String])
+ case BinaryType =>
Some(Gen.listOf(Arbitrary.arbitrary[Byte]).map(_.toArray))
--- End diff --
Note that I mapped a list into an Array instead of using
`Arbitrary.arbitrary[Array[Byte]]` because the latter seems to run into a
possible ScalaCheck NPE bug when we wrap the resulting generator to sometimes
return nulls. I've filed https://github.com/rickynils/scalacheck/issues/177 to
try to investigate this upstream. AFAIK the only downside to the workaround
here is that we lose some of the failing test case minimization benefits that
ScalaCheck provides.
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