rangadi commented on code in PR #38286:
URL: https://github.com/apache/spark/pull/38286#discussion_r997526883
##########
connector/protobuf/src/test/scala/org/apache/spark/sql/protobuf/ProtobufCatalystDataConversionSuite.scala:
##########
@@ -99,26 +115,32 @@ class ProtobufCatalystDataConversionSuite
StructType(StructField("bytes_type", BinaryType, nullable = true) :: Nil),
StructType(StructField("string_type", StringType, nullable = true) :: Nil))
- private val catalystTypesToProtoMessages: Map[DataType, String] = Map(
- IntegerType -> "IntegerMsg",
- DoubleType -> "DoubleMsg",
- FloatType -> "FloatMsg",
- BinaryType -> "BytesMsg",
- StringType -> "StringMsg")
+ private val catalystTypesToProtoMessages: Map[DataType, (String, Any)] = Map(
+ IntegerType -> ("IntegerMsg", 0),
+ DoubleType -> ("DoubleMsg", 0.0d),
+ FloatType -> ("FloatMsg", 0.0f),
+ BinaryType -> ("BytesMsg", ByteString.empty().toByteArray),
+ StringType -> ("StringMsg", ""))
testingTypes.foreach { dt =>
val seed = 1 + scala.util.Random.nextInt((1024 - 1) + 1)
- val filePath = testFile("protobuf/catalyst_types.desc").replace("file:/",
"/")
test(s"single $dt with seed $seed") {
+
+ val (messageName, defaultValue) =
catalystTypesToProtoMessages(dt.fields(0).dataType)
+
val rand = new scala.util.Random(seed)
- val data = RandomDataGenerator.forType(dt, rand = rand).get.apply()
+ val generator = RandomDataGenerator.forType(dt, rand = rand).get
+ var data = generator()
+ while (data.asInstanceOf[Row].get(0) == defaultValue) // Do not use
default values, since
Review Comment:
Or just rerunning handful of times triggers this. `RandomDataGenerator`
intentionally returns edge values like '0' often (50% of the time by default).
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