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Posted to reviews@spark.apache.org by "shujingyang-db (via GitHub)" <gi...@apache.org> on 2024/03/15 20:55:46 UTC
[PR] [SPARK-47309][SQL] XML: Add schema inference tests for value tags [spark]
shujingyang-db opened a new pull request, #45538:
URL: https://github.com/apache/spark/pull/45538
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Add schema inference tags for corrupt records, null values and value tags. For value tags, this PR adds the following tests:
1. Conflict between primitive types conflict
2. Root-level value tag
3. empty value tag in some rows
4. array of value tags:
1) values split into multiple lines
2) interspersed in nested structs: empty fields and optional fields in structs
3) interspersed in arrays and value tags: empty fields and optional fields in structs
4) name conflict
5) CDATA and comments
6) no spaces / some spaces / whitespaces between valueTags and elements
### Why are the changes needed?
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This is a test-only change.
### Does this PR introduce _any_ user-facing change?
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No
### How was this patch tested?
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This is a test-only change.
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Re: [PR] [SPARK-47309][SQL] XML: Add schema inference tests for value tags [spark]
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #45538:
URL: https://github.com/apache/spark/pull/45538#issuecomment-2008486564
Merged to master.
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Re: [PR] [SPARK-47309][SQL] XML: Add schema inference tests for value tags [spark]
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon closed pull request #45538: [SPARK-47309][SQL] XML: Add schema inference tests for value tags
URL: https://github.com/apache/spark/pull/45538
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Re: [PR] [SPARK-47309][SQL] XML: Add schema inference tests for value tags [spark]
Posted by "sandip-db (via GitHub)" <gi...@apache.org>.
sandip-db commented on code in PR #45538:
URL: https://github.com/apache/spark/pull/45538#discussion_r1529515496
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/xml/XmlInferSchemaSuite.scala:
##########
@@ -293,4 +305,323 @@ class XmlInferSchemaSuite extends QueryTest with SharedSparkSession with TestXml
assert(emptyDF.schema === expectedSchema)
}
+ test("nulls in arrays") {
+ val expectedSchema = StructType(
+ StructField(
+ "field1",
+ ArrayType(
+ new StructType()
+ .add("array1", ArrayType(new StructType().add("array2", ArrayType(StringType))))
+ )
+ ) ::
+ StructField(
+ "field2",
+ ArrayType(
+ new StructType()
+ .add("array1", ArrayType(StructType(StructField("Test", LongType) :: Nil)))
+ )
+ ) :: Nil
+ )
+ val expectedAns = Seq(
+ Row(Seq(Row(Seq(Row(Seq("value1", "value2")), Row(null))), Row(null)), null),
+ Row(null, Seq(Row(null), Row(Seq(Row(1), Row(null))))),
+ Row(Seq(Row(null), Row(Seq(Row(null)))), Seq(Row(null)))
+ )
+ val xmlDF = readData(nullsInArrays)
+ assert(xmlDF.schema === expectedSchema)
+ checkAnswer(xmlDF, expectedAns)
+ }
+
+ test("corrupt records: fail fast mode") {
+ // fail fast mode is covered in the testcase: DSL test for failing fast in XmlSuite
+ val schemaOne = StructType(
+ StructField("a", StringType, true) ::
+ StructField("b", StringType, true) ::
+ StructField("c", StringType, true) :: Nil
+ )
+ // `DROPMALFORMED` mode should skip corrupt records
+ val xmlDFOne = readData(corruptRecords, Map("mode" -> "DROPMALFORMED"))
+ checkAnswer(
+ xmlDFOne,
+ Row("1", "2", null) ::
+ Row("str_a_4", "str_b_4", "str_c_4") :: Nil
+ )
+ assert(xmlDFOne.schema === schemaOne)
+ }
+
+ test("turn non-nullable schema into a nullable schema") {
+ // XML field is missing.
+ val missingFieldInput = """<ROW><c1>1</c1></ROW>"""
+ val missingFieldInputDS =
+ spark.createDataset(spark.sparkContext.parallelize(missingFieldInput :: Nil))(Encoders.STRING)
+ // XML filed is null.
+ val nullValueInput = """<ROW><c1>1</c1><c2/></ROW>"""
+ val nullValueInputDS =
+ spark.createDataset(spark.sparkContext.parallelize(nullValueInput :: Nil))(Encoders.STRING)
+
+ val schema = StructType(
+ Seq(
+ StructField("c1", IntegerType, nullable = false),
+ StructField("c2", IntegerType, nullable = false)
+ )
+ )
+ val expected = schema.asNullable
+
+ Seq(missingFieldInputDS, nullValueInputDS).foreach { xmlStringDS =>
+ Seq("DROPMALFORMED", "FAILFAST", "PERMISSIVE").foreach { mode =>
+ val df = spark.read
+ .option("mode", mode)
+ .option("rowTag", "ROW")
+ .schema(schema)
+ .xml(xmlStringDS)
+ assert(df.schema == expected)
+ checkAnswer(df, Row(1, null) :: Nil)
+ }
+ withSQLConf(SQLConf.LEGACY_RESPECT_NULLABILITY_IN_TEXT_DATASET_CONVERSION.key -> "true") {
+ checkAnswer(
+ spark.read
+ .schema(
+ StructType(
+ StructField("c1", LongType, nullable = false) ::
+ StructField("c2", LongType, nullable = false) :: Nil
+ )
+ )
+ .option("rowTag", "ROW")
+ .option("mode", "DROPMALFORMED")
+ .xml(xmlStringDS),
+ // It is for testing legacy configuration. This is technically a bug as
+ // `0` has to be `null` but the schema is non-nullable.
+ Row(1, 0)
+ )
+ }
+ }
+ }
+
+ test("XML with partitions") {
+ def makePartition(rdd: RDD[String], parent: File, partName: String, partValue: Any): File = {
+ val p = new File(parent, s"$partName=${partValue.toString}")
+ rdd.saveAsTextFile(p.getCanonicalPath)
+ p
+ }
+
+ withTempPath(root => {
+ withTempView("test_myxml_with_part") {
+ val d1 = new File(root, "d1=1")
+ // root/dt=1/col1=abc
+ makePartition(
+ sparkContext.parallelize(2 to 5).map(i => s"""<ROW><a>1</a><b>str$i</b></ROW>"""),
+ d1,
+ "col1",
+ "abc"
+ )
+
+ // root/dt=1/col1=abd
Review Comment:
nit:
```suggestion
// root/d1=1/col1=abd
```
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/xml/XmlInferSchemaSuite.scala:
##########
@@ -293,4 +305,323 @@ class XmlInferSchemaSuite extends QueryTest with SharedSparkSession with TestXml
assert(emptyDF.schema === expectedSchema)
}
+ test("nulls in arrays") {
+ val expectedSchema = StructType(
+ StructField(
+ "field1",
+ ArrayType(
+ new StructType()
+ .add("array1", ArrayType(new StructType().add("array2", ArrayType(StringType))))
+ )
+ ) ::
+ StructField(
+ "field2",
+ ArrayType(
+ new StructType()
+ .add("array1", ArrayType(StructType(StructField("Test", LongType) :: Nil)))
+ )
+ ) :: Nil
+ )
+ val expectedAns = Seq(
+ Row(Seq(Row(Seq(Row(Seq("value1", "value2")), Row(null))), Row(null)), null),
+ Row(null, Seq(Row(null), Row(Seq(Row(1), Row(null))))),
+ Row(Seq(Row(null), Row(Seq(Row(null)))), Seq(Row(null)))
+ )
+ val xmlDF = readData(nullsInArrays)
+ assert(xmlDF.schema === expectedSchema)
+ checkAnswer(xmlDF, expectedAns)
+ }
+
+ test("corrupt records: fail fast mode") {
+ // fail fast mode is covered in the testcase: DSL test for failing fast in XmlSuite
+ val schemaOne = StructType(
+ StructField("a", StringType, true) ::
+ StructField("b", StringType, true) ::
+ StructField("c", StringType, true) :: Nil
+ )
+ // `DROPMALFORMED` mode should skip corrupt records
+ val xmlDFOne = readData(corruptRecords, Map("mode" -> "DROPMALFORMED"))
+ checkAnswer(
+ xmlDFOne,
+ Row("1", "2", null) ::
+ Row("str_a_4", "str_b_4", "str_c_4") :: Nil
+ )
+ assert(xmlDFOne.schema === schemaOne)
+ }
+
+ test("turn non-nullable schema into a nullable schema") {
+ // XML field is missing.
+ val missingFieldInput = """<ROW><c1>1</c1></ROW>"""
+ val missingFieldInputDS =
+ spark.createDataset(spark.sparkContext.parallelize(missingFieldInput :: Nil))(Encoders.STRING)
+ // XML filed is null.
+ val nullValueInput = """<ROW><c1>1</c1><c2/></ROW>"""
+ val nullValueInputDS =
+ spark.createDataset(spark.sparkContext.parallelize(nullValueInput :: Nil))(Encoders.STRING)
+
+ val schema = StructType(
+ Seq(
+ StructField("c1", IntegerType, nullable = false),
+ StructField("c2", IntegerType, nullable = false)
+ )
+ )
+ val expected = schema.asNullable
+
+ Seq(missingFieldInputDS, nullValueInputDS).foreach { xmlStringDS =>
+ Seq("DROPMALFORMED", "FAILFAST", "PERMISSIVE").foreach { mode =>
+ val df = spark.read
+ .option("mode", mode)
+ .option("rowTag", "ROW")
+ .schema(schema)
+ .xml(xmlStringDS)
+ assert(df.schema == expected)
+ checkAnswer(df, Row(1, null) :: Nil)
+ }
+ withSQLConf(SQLConf.LEGACY_RESPECT_NULLABILITY_IN_TEXT_DATASET_CONVERSION.key -> "true") {
+ checkAnswer(
+ spark.read
+ .schema(
+ StructType(
+ StructField("c1", LongType, nullable = false) ::
+ StructField("c2", LongType, nullable = false) :: Nil
+ )
+ )
+ .option("rowTag", "ROW")
+ .option("mode", "DROPMALFORMED")
+ .xml(xmlStringDS),
+ // It is for testing legacy configuration. This is technically a bug as
+ // `0` has to be `null` but the schema is non-nullable.
+ Row(1, 0)
+ )
+ }
+ }
+ }
+
+ test("XML with partitions") {
+ def makePartition(rdd: RDD[String], parent: File, partName: String, partValue: Any): File = {
+ val p = new File(parent, s"$partName=${partValue.toString}")
+ rdd.saveAsTextFile(p.getCanonicalPath)
+ p
+ }
+
+ withTempPath(root => {
+ withTempView("test_myxml_with_part") {
+ val d1 = new File(root, "d1=1")
+ // root/dt=1/col1=abc
+ makePartition(
+ sparkContext.parallelize(2 to 5).map(i => s"""<ROW><a>1</a><b>str$i</b></ROW>"""),
+ d1,
+ "col1",
+ "abc"
+ )
+
+ // root/dt=1/col1=abd
+ makePartition(
+ sparkContext.parallelize(6 to 10).map(i => s"""<ROW><a>1</a><c>str$i</c></ROW>"""),
+ d1,
+ "col1",
+ "abd"
+ )
+ val expectedSchema = new StructType()
+ .add("a", LongType)
+ .add("b", StringType)
+ .add("c", StringType)
+ .add("d1", IntegerType)
+ .add("col1", StringType)
+
+ val df = spark.read.option("rowTag", "ROW").xml(root.getAbsolutePath)
+ assert(df.schema === expectedSchema)
+ assert(df.where(col("d1") === 1).where(col("col1") === "abc").select("a").count() == 4)
+ assert(df.where(col("d1") === 1).where(col("col1") === "abd").select("a").count() == 5)
+ assert(df.where(col("d1") === 1).select("a").count() == 9)
+ }
+ })
+ }
+
+ test("value tag - type conflict and root level value tags") {
+ val xmlDF = readData(valueTagsTypeConflict, ignoreSurroundingSpacesOptions)
+ val expectedSchema = new StructType()
+ .add(valueTagName, ArrayType(StringType))
+ .add(
+ "a",
+ new StructType()
+ .add(valueTagName, LongType)
+ .add("b", new StructType().add(valueTagName, StringType).add("c", LongType))
+ )
+ assert(xmlDF.schema == expectedSchema)
+ val expectedAns = Seq(
+ Row(Seq("13.1", "string"), Row(11, Row("true", 1))),
+ Row(Seq("string", "true"), Row(21474836470L, Row("false", 2))),
+ Row(Seq("92233720368547758070"), Row(null, Row("12", 3)))
+ )
+ checkAnswer(xmlDF, expectedAns)
+ }
+
+ test("value tag - spaces and empty values") {
+ val expectedSchema = new StructType()
+ .add(valueTagName, ArrayType(StringType))
+ .add("a", new StructType().add(valueTagName, StringType).add("b", LongType))
+ // even though we don't ignore the surrounding spaces of characters,
+ // we won't put whitespaces as value tags :)
+ val xmlDFWSpaces =
+ readData(emptyValueTags, notIgnoreSurroundingSpacesOptions)
+ val xmlDFWOSpaces = readData(emptyValueTags, ignoreSurroundingSpacesOptions)
+ assert(xmlDFWSpaces.schema == expectedSchema)
+ assert(xmlDFWOSpaces.schema == expectedSchema)
+
+ val expectedAnsWSpaces = Seq(
+ Row(Seq("\n str1\n ", "str2\n"), Row(null, 1)),
+ Row(null, Row(" value", null)),
+ Row(null, Row(null, 3)),
+ Row(Seq("\n str3\n"), Row(null, 4))
+ )
+ checkAnswer(xmlDFWSpaces, expectedAnsWSpaces)
+ val expectedAnsWOSpaces = Seq(
+ Row(Seq("str1", "str2"), Row(null, 1)),
+ Row(null, Row("value", null)),
+ Row(null, Row(null, 3)),
+ Row(Seq("str3"), Row(null, 4))
+ )
+ checkAnswer(xmlDFWOSpaces, expectedAnsWOSpaces)
+ }
+
+ test("value tags - multiple lines") {
+ val xmlDF = readData(multilineValueTags, ignoreSurroundingSpacesOptions)
+ val expectedSchema =
+ new StructType().add(valueTagName, ArrayType(StringType)).add("a", LongType)
+ val expectedAns = Seq(
+ Row(Seq("value1", "value2"), 1),
+ Row(Seq("value3\n value4"), 1)
+ )
+ assert(xmlDF.schema == expectedSchema)
+ checkAnswer(xmlDF, expectedAns)
+ }
+
+ test("value tags - around structs") {
+ val xmlDF = readData(valueTagsAroundStructs)
+ val expectedSchema = new StructType()
+ .add(valueTagName, ArrayType(StringType))
+ .add(
+ "a",
+ new StructType()
+ .add(valueTagName, ArrayType(StringType))
+ .add("b", new StructType().add(valueTagName, LongType).add("c", LongType))
+ )
+
+ assert(xmlDF.schema == expectedSchema)
+ val expectedAns = Seq(
+ Row(
+ Seq("value1", "value5"),
+ Row(Seq("value2", "value4"), Row(3, 1))
+ ),
+ Row(
+ Seq("value6"),
+ Row(Seq("value4", "value5"), Row(null, null))
+ ),
+ Row(
+ Seq("value1", "value5"),
+ Row(Seq("value2", "value4"), Row(3, null))
+ ),
+ Row(
+ Seq("value1"),
+ Row(Seq("value2", "value4"), Row(3, null))
+ )
+ )
+ checkAnswer(xmlDF, expectedAns)
+ }
+
+ test("value tags - around arrays") {
+ val xmlDF = readData(valueTagsAroundArrays)
+ val expectedSchema = new StructType()
+ .add(valueTagName, ArrayType(StringType))
+ .add(
+ "array1",
+ ArrayType(
+ new StructType()
+ .add(valueTagName, ArrayType(StringType))
+ .add(
+ "array2",
+ ArrayType(new StructType()
+ // The value tag is not of long type due to:
+ // When determining
+ .add(valueTagName, ArrayType(StringType))
Review Comment:
Update comment.. why it is not LongType?
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/xml/XmlInferSchemaSuite.scala:
##########
@@ -293,4 +305,323 @@ class XmlInferSchemaSuite extends QueryTest with SharedSparkSession with TestXml
assert(emptyDF.schema === expectedSchema)
}
+ test("nulls in arrays") {
+ val expectedSchema = StructType(
+ StructField(
+ "field1",
+ ArrayType(
+ new StructType()
+ .add("array1", ArrayType(new StructType().add("array2", ArrayType(StringType))))
+ )
+ ) ::
+ StructField(
+ "field2",
+ ArrayType(
+ new StructType()
+ .add("array1", ArrayType(StructType(StructField("Test", LongType) :: Nil)))
+ )
+ ) :: Nil
+ )
+ val expectedAns = Seq(
+ Row(Seq(Row(Seq(Row(Seq("value1", "value2")), Row(null))), Row(null)), null),
+ Row(null, Seq(Row(null), Row(Seq(Row(1), Row(null))))),
+ Row(Seq(Row(null), Row(Seq(Row(null)))), Seq(Row(null)))
+ )
+ val xmlDF = readData(nullsInArrays)
+ assert(xmlDF.schema === expectedSchema)
+ checkAnswer(xmlDF, expectedAns)
+ }
+
+ test("corrupt records: fail fast mode") {
+ // fail fast mode is covered in the testcase: DSL test for failing fast in XmlSuite
+ val schemaOne = StructType(
+ StructField("a", StringType, true) ::
+ StructField("b", StringType, true) ::
+ StructField("c", StringType, true) :: Nil
+ )
+ // `DROPMALFORMED` mode should skip corrupt records
+ val xmlDFOne = readData(corruptRecords, Map("mode" -> "DROPMALFORMED"))
+ checkAnswer(
+ xmlDFOne,
+ Row("1", "2", null) ::
+ Row("str_a_4", "str_b_4", "str_c_4") :: Nil
+ )
+ assert(xmlDFOne.schema === schemaOne)
+ }
+
+ test("turn non-nullable schema into a nullable schema") {
+ // XML field is missing.
+ val missingFieldInput = """<ROW><c1>1</c1></ROW>"""
+ val missingFieldInputDS =
+ spark.createDataset(spark.sparkContext.parallelize(missingFieldInput :: Nil))(Encoders.STRING)
+ // XML filed is null.
+ val nullValueInput = """<ROW><c1>1</c1><c2/></ROW>"""
+ val nullValueInputDS =
+ spark.createDataset(spark.sparkContext.parallelize(nullValueInput :: Nil))(Encoders.STRING)
+
+ val schema = StructType(
+ Seq(
+ StructField("c1", IntegerType, nullable = false),
+ StructField("c2", IntegerType, nullable = false)
+ )
+ )
+ val expected = schema.asNullable
+
+ Seq(missingFieldInputDS, nullValueInputDS).foreach { xmlStringDS =>
+ Seq("DROPMALFORMED", "FAILFAST", "PERMISSIVE").foreach { mode =>
+ val df = spark.read
+ .option("mode", mode)
+ .option("rowTag", "ROW")
+ .schema(schema)
+ .xml(xmlStringDS)
+ assert(df.schema == expected)
+ checkAnswer(df, Row(1, null) :: Nil)
+ }
+ withSQLConf(SQLConf.LEGACY_RESPECT_NULLABILITY_IN_TEXT_DATASET_CONVERSION.key -> "true") {
+ checkAnswer(
+ spark.read
+ .schema(
+ StructType(
+ StructField("c1", LongType, nullable = false) ::
+ StructField("c2", LongType, nullable = false) :: Nil
+ )
+ )
+ .option("rowTag", "ROW")
+ .option("mode", "DROPMALFORMED")
+ .xml(xmlStringDS),
+ // It is for testing legacy configuration. This is technically a bug as
+ // `0` has to be `null` but the schema is non-nullable.
+ Row(1, 0)
+ )
+ }
+ }
+ }
+
+ test("XML with partitions") {
+ def makePartition(rdd: RDD[String], parent: File, partName: String, partValue: Any): File = {
+ val p = new File(parent, s"$partName=${partValue.toString}")
+ rdd.saveAsTextFile(p.getCanonicalPath)
+ p
+ }
+
+ withTempPath(root => {
+ withTempView("test_myxml_with_part") {
+ val d1 = new File(root, "d1=1")
+ // root/dt=1/col1=abc
Review Comment:
nit:
```suggestion
// root/d1=1/col1=abc
```
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Re: [PR] [SPARK-47309][SQL] XML: Add schema inference tests for value tags [spark]
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #45538:
URL: https://github.com/apache/spark/pull/45538#issuecomment-2008486755
Merged to master.
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