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[SPARK-25134][SQL] Csv column pruning with checking of headers throws incorrect error #22123

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[SPARK-25134][SQL] Csv column pruning with checking of headers throws incorrect error #22123

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dcd9ac4
if csv column-pruning is turned on header should be checked with requ…
koertkuipers Aug 16, 2018
c4179a9
update jira reference in unit test
koertkuipers Aug 16, 2018
09c986c
remove test for check header and projection with column pruning disabled
koertkuipers Aug 17, 2018
cd18ed2
also check multiLine codepath and selecting empty schema with count
koertkuipers Aug 19, 2018
f2eb1df
remove checkHeader and use checkHeaderColumnNames directly
koertkuipers Aug 20, 2018
667db3c
use style convention of explicit vals
koertkuipers Aug 20, 2018
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13 changes: 8 additions & 5 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVDataSource.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -54,7 +54,8 @@ abstract class CSVDataSource extends Serializable {
requiredSchema: StructType,
// Actual schema of data in the csv file
dataSchema: StructType,
caseSensitive: Boolean): Iterator[InternalRow]
caseSensitive: Boolean,
columnPruning: Boolean): Iterator[InternalRow]

/**
* Infers the schema from `inputPaths` files.
Expand Down Expand Up @@ -211,7 +212,8 @@ object TextInputCSVDataSource extends CSVDataSource {
parser: UnivocityParser,
requiredSchema: StructType,
dataSchema: StructType,
caseSensitive: Boolean): Iterator[InternalRow] = {
caseSensitive: Boolean,
columnPruning: Boolean): Iterator[InternalRow] = {
val lines = {
val linesReader = new HadoopFileLinesReader(file, conf)
Option(TaskContext.get()).foreach(_.addTaskCompletionListener[Unit](_ => linesReader.close()))
Expand All @@ -230,7 +232,7 @@ object TextInputCSVDataSource extends CSVDataSource {
CSVDataSource.checkHeader(
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@HyukjinKwon HyukjinKwon Aug 20, 2018 •
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Can we remove CSVDataSource.checkHeader and switch to CSVDataSource.checkHeaderColumnNames? Looks CSVDataSource.checkHeader is an overkill and makes hard to read the code.

header,
parser.tokenizer,
dataSchema,
if (columnPruning) requiredSchema else dataSchema,
file.filePath,
parser.options.enforceSchema,
caseSensitive)
Expand Down Expand Up @@ -308,10 +310,11 @@ object MultiLineCSVDataSource extends CSVDataSource {
parser: UnivocityParser,
requiredSchema: StructType,
dataSchema: StructType,
caseSensitive: Boolean): Iterator[InternalRow] = {
caseSensitive: Boolean,
columnPruning: Boolean): Iterator[InternalRow] = {
def checkHeader(header: Array[String]): Unit = {
CSVDataSource.checkHeaderColumnNames(
dataSchema,
if (columnPruning) requiredSchema else dataSchema,
header,
file.filePath,
parser.options.enforceSchema,
Expand Down
4 changes: 3 additions & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala
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Expand Up @@ -131,6 +131,7 @@ class CSVFileFormat extends TextBasedFileFormat with DataSourceRegister {
)
}
val caseSensitive = sparkSession.sessionState.conf.caseSensitiveAnalysis
val columnPruning = sparkSession.sessionState.conf.csvColumnPruning

(file: PartitionedFile) => {
val conf = broadcastedHadoopConf.value.value
Expand All @@ -144,7 +145,8 @@ class CSVFileFormat extends TextBasedFileFormat with DataSourceRegister {
parser,
requiredSchema,
dataSchema,
caseSensitive)
caseSensitive,
columnPruning)
}
}

Expand Down
19 changes: 19 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala
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Expand Up @@ -1603,6 +1603,25 @@ class CSVSuite extends QueryTest with SharedSQLContext with SQLTestUtils with Te
.exists(msg => msg.getRenderedMessage.contains("CSV header does not conform to the schema")))
}

test("SPARK-25134: check header on parsing of dataset with projection and column pruning") {
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@gatorsmile gatorsmile Aug 20, 2018

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Also need a test case for checking enforceSchema works well when column pruning is on.

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@koertkuipers koertkuipers Aug 20, 2018

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it seems enforceSchema always kind of "works" because it simply means it ignores the headers.
what do we expect to verify in the test?

withSQLConf(SQLConf.CSV_PARSER_COLUMN_PRUNING.key -> "true") {
withTempPath { path =>
val dir = path.getAbsolutePath
Seq(("a", "b")).toDF("columnA", "columnB").write
.format("csv")
.option("header", true)
.save(dir)
checkAnswer(spark.read
.format("csv")
.option("header", true)
.option("enforceSchema", false)
.load(dir)
.select("columnA"),
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@MaxGekk MaxGekk Aug 18, 2018

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Could you check a corner case when required Schema is empty. For example, .option("enforceSchema", false) + count().

Row("a"))
}
}
}

test("SPARK-24645 skip parsing when columnPruning enabled and partitions scanned only") {
withSQLConf(SQLConf.CSV_PARSER_COLUMN_PRUNING.key -> "true") {
withTempPath { path =>
Expand Down