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[SPARK-30810][SQL] Parses and convert a CSV Dataset having different column from 'value' in csv(dataset) API #27561

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[SPARK-30810][SQL] Parses and convert a CSV Dataset having different column from 'value' in csv(dataset) API #27561

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Parses and convert a CSV Dataset having different column from 'value'…
HyukjinKwon Feb 13, 2020
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Another approach
HyukjinKwon Feb 14, 2020
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7 changes: 4 additions & 3 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVUtils.scala
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Expand Up @@ -33,11 +33,12 @@ object CSVUtils {
// with the one below, `filterCommentAndEmpty` but execution path is different. One of them
// might have to be removed in the near future if possible.
import lines.sqlContext.implicits._
val nonEmptyLines = lines.filter(length(trim($"value")) > 0)
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@HyukjinKwon HyukjinKwon Feb 14, 2020

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@MaxGekk and @cloud-fan, I came up with a better idea to avoid relying on string format in col. Can you take a look again? I think this way is safer.

val aliased = lines.toDF("value")
val nonEmptyLines = aliased.filter(length(trim($"value")) > 0)
if (options.isCommentSet) {
nonEmptyLines.filter(!$"value".startsWith(options.comment.toString))
nonEmptyLines.filter(!$"value".startsWith(options.comment.toString)).as[String]
} else {
nonEmptyLines
nonEmptyLines.as[String]
}
}

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7 changes: 7 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala
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Expand Up @@ -2294,6 +2294,13 @@ abstract class CSVSuite extends QueryTest with SharedSparkSession with TestCsvDa
}
}
}

test("SPARK-30810: parses and convert a CSV Dataset having different column from 'value'") {
val ds = spark.range(2).selectExpr("concat('a,b,', id) AS `a.text`").as[String]
val csv = spark.read.option("header", true).option("inferSchema", true).csv(ds)
assert(csv.schema.fieldNames === Seq("a", "b", "0"))
checkAnswer(csv, Row("a", "b", 1))
}
}

class CSVv1Suite extends CSVSuite {
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