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[SPARK-31878][SQL] Create date formatter only once in HiveResult #28687

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[SPARK-31878][SQL] Create date formatter only once in HiveResult #28687

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ed4d928
Add test
MaxGekk May 31, 2020
9dffb04
def -> val
MaxGekk May 31, 2020
a1da8a7
Use FastDateFormat instead of SimpleDateFormat
MaxGekk May 31, 2020
b97a84b
Remove zoneId
MaxGekk May 31, 2020
6984544
Correct the comment for dateFormatter
MaxGekk Jun 3, 2020
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8 changes: 7 additions & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/execution/HiveResult.scala
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Expand Up @@ -73,7 +73,13 @@ object HiveResult {
}

private def zoneId = DateTimeUtils.getZoneId(SQLConf.get.sessionLocalTimeZone)
private def dateFormatter = DateFormatter(zoneId)
// Date formatting does not depend on time zone ID because it converts local days
// since the epoch to local date string. Time zone id does matter only in parsing
// when the parser has to handle special values like `now`, `yesterday` and etc.
// Here, `dateFormatter` is used only for formatting, so, we can initialize it by
// any time zone once, for instance, by the current session time zone. And we can
// reuse it even when the session time zone might be changed.
private val dateFormatter = DateFormatter(zoneId)

@MaxGekk MaxGekk May 31, 2020 •
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Just in case, can hiveResultString() or toHiveString() be called from multiple threads in parallel? If so, we cannot use SimpleDateFormat here because it is not thread-safe. In that case, dateFormatter must use FastDateFormat because it is thread-safe.

@juliuszsompolski juliuszsompolski Jun 2, 2020

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Yes, it can be called concurrently (e.g. by concurrent thriftserver queries).

@MaxGekk MaxGekk Jun 3, 2020

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ok. I use FastDateFormat for java.sql.Date which is thread-safe and DateTimeFormatter for java.time.LocalDate. The former one is thread-safe as well. Should be fine.

private def timestampFormatter = TimestampFormatter.getFractionFormatter(zoneId)

/** Formats a datum (based on the given data type) and returns the string representation. */
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22 changes: 14 additions & 8 deletions sql/core/src/test/scala/org/apache/spark/sql/execution/HiveResultSuite.scala
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Expand Up @@ -17,21 +17,27 @@

package org.apache.spark.sql.execution

import org.apache.spark.sql.catalyst.util.DateTimeTestUtils
import org.apache.spark.sql.connector.InMemoryTableCatalog
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.test.{ExamplePoint, ExamplePointUDT, SharedSparkSession}

class HiveResultSuite extends SharedSparkSession {
import testImplicits._

test("date formatting in hive result") {
val dates = Seq("2018-12-28", "1582-10-03", "1582-10-04", "1582-10-15")
val df = dates.toDF("a").selectExpr("cast(a as date) as b")
val executedPlan1 = df.queryExecution.executedPlan
val result = HiveResult.hiveResultString(executedPlan1)
assert(result == dates)
val executedPlan2 = df.selectExpr("array(b)").queryExecution.executedPlan
val result2 = HiveResult.hiveResultString(executedPlan2)
assert(result2 == dates.map(x => s"[$x]"))
DateTimeTestUtils.outstandingTimezonesIds.foreach { zoneId =>
withSQLConf(SQLConf.SESSION_LOCAL_TIMEZONE.key -> zoneId) {
val dates = Seq("2018-12-28", "1582-10-03", "1582-10-04", "1582-10-15")
val df = dates.toDF("a").selectExpr("cast(a as date) as b")
val executedPlan1 = df.queryExecution.executedPlan
val result = HiveResult.hiveResultString(executedPlan1)
assert(result == dates)
val executedPlan2 = df.selectExpr("array(b)").queryExecution.executedPlan
val result2 = HiveResult.hiveResultString(executedPlan2)
assert(result2 == dates.map(x => s"[$x]"))
}
}
}

test("timestamp formatting in hive result") {
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