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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2020/05/14 06:36:05 UTC
[GitHub] [spark] cloud-fan opened a new pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
cloud-fan opened a new pull request #28526:
URL: https://github.com/apache/spark/pull/28526
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### What changes were proposed in this pull request?
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When reading/writing datetime values that before the rebase switch day, from/to Avro/Parquet files, fail by default and ask users to set a config to explicitly do rebase or not.
### Why are the changes needed?
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Rebase or not rebase have different behaviors and we should let users decide it explicitly. In most cases, users won't hit this exception as it only affects ancient datetime values.
### Does this PR introduce _any_ user-facing change?
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Yes, now users will see an error when reading/writing dates before 1582-10-15 or timestamps before 1900-01-01 from/to Parquet/Avro files, with an error message to ask setting a config.
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updated tests
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[GitHub] [spark] HyukjinKwon commented on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #28526:
URL: https://github.com/apache/spark/pull/28526#issuecomment-629021118
FYI,tThis seems not completely fixed yet due to the cached `.m2/repository`, see also https://issues.apache.org/jira/browse/SPARK-31693?focusedCommentId=17107856&page=com.atlassian.jira.plugin.system.issuetabpanels%3Acomment-tabpanel#comment-17107856
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[GitHub] [spark] cloud-fan commented on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on pull request #28526:
URL: https://github.com/apache/spark/pull/28526#issuecomment-628421014
cc @HyukjinKwon @MaxGekk
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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/28526#issuecomment-629020394
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[GitHub] [spark] SparkQA commented on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #28526:
URL: https://github.com/apache/spark/pull/28526#issuecomment-629131990
**[Test build #5018 has finished](https://amplab.cs.berkeley.edu/jenkins/job/NewSparkPullRequestBuilder/5018/testReport)** for PR 28526 at commit [`9f14144`](https://github.com/apache/spark/commit/9f14144d191c8c41d8b3bd9585d78eb7ddae8407).
* This patch **fails build dependency tests**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class AvroDeserializer(`
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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/28526#issuecomment-629146816
**[Test build #122666 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/122666/testReport)** for PR 28526 at commit [`9f14144`](https://github.com/apache/spark/commit/9f14144d191c8c41d8b3bd9585d78eb7ddae8407).
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[GitHub] [spark] dongjoon-hyun commented on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on pull request #28526:
URL: https://github.com/apache/spark/pull/28526#issuecomment-629034425
Ya. The failure jobs are on the same broken Jenkins machine, `amp-jenkins-worker-05`.
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**[Test build #5036 has finished](https://amplab.cs.berkeley.edu/jenkins/job/NewSparkPullRequestBuilder/5036/testReport)** for PR 28526 at commit [`9f14144`](https://github.com/apache/spark/commit/9f14144d191c8c41d8b3bd9585d78eb7ddae8407).
* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class AvroDeserializer(`
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[GitHub] [spark] HyukjinKwon edited a comment on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
Posted by GitBox <gi...@apache.org>.
HyukjinKwon edited a comment on pull request #28526:
URL: https://github.com/apache/spark/pull/28526#issuecomment-629021118
FYI, the issue seems not completely fixed yet due to the cached `.m2/repository`, see also https://issues.apache.org/jira/browse/SPARK-31693?focusedCommentId=17107856&page=com.atlassian.jira.plugin.system.issuetabpanels%3Acomment-tabpanel#comment-17107856
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* This patch **fails build dependency tests**.
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* This patch adds the following public classes _(experimental)_:
* `class AvroDeserializer(`
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[GitHub] [spark] HyukjinKwon commented on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
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retest this please
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* This patch **fails build dependency tests**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class AvroDeserializer(`
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[GitHub] [spark] dongjoon-hyun commented on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
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FYI, the dependency failure will be fixed by the following.
- https://github.com/apache/spark/pull/28532
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finally, jenkins pass... merging to 3.0!
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retest this please
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retest this please
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[GitHub] [spark] dongjoon-hyun edited a comment on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
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dongjoon-hyun edited a comment on pull request #28526:
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Ya. The failure jobs are on the same broken Jenkins machine, `amp-jenkins-worker-05`.
And, the running jobs are on `amp-jenkins-worker-03` and `amp-jenkins-worker-04`.
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[GitHub] [spark] cloud-fan commented on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on pull request #28526:
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Yea, all the conflicts are caused by the different name of `DateTimeUtils.toMillis` in 3.0
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[GitHub] [spark] cloud-fan commented on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
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cloud-fan commented on pull request #28526:
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retest this please
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[GitHub] [spark] dongjoon-hyun edited a comment on pull request #28526: [SPARK-31405][SQL][3.0] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
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dongjoon-hyun edited a comment on pull request #28526:
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@cloud-fan . You can see `HiveExternalCatalogVersionsSuite` in the above two runs consistently.
cc @viirya .
We need https://github.com/apache/spark/pull/28536 .
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retest this please
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@cloud-fan . You can see `HiveExternalCatalogVersionsSuite` in the above two runs.
cc @viirya .
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@cloud-fan . You can see `HiveExternalCatalogVersionsSuite` in the above two runs consistently.
cc @viirya .
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Posted by GitBox <gi...@apache.org>.
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Many ..
```diff
diff --cc external/avro/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala
index 27206edb287,1d18594fd34..00000000000
--- a/external/avro/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala
+++ b/external/avro/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala
@@@ -110,22 -116,13 +116,29 @@@ class AvroDeserializer
case (LONG, TimestampType) => avroType.getLogicalType match {
// For backward compatibility, if the Avro type is Long and it is not logical type
// (the `null` case), the value is processed as timestamp type with millisecond precision.
++<<<<<<< HEAD
+ case null | _: TimestampMillis if rebaseDateTime => (updater, ordinal, value) =>
+ val millis = value.asInstanceOf[Long]
+ val micros = DateTimeUtils.fromMillis(millis)
+ val rebasedMicros = rebaseJulianToGregorianMicros(micros)
+ updater.setLong(ordinal, rebasedMicros)
+ case null | _: TimestampMillis => (updater, ordinal, value) =>
+ val millis = value.asInstanceOf[Long]
+ val micros = DateTimeUtils.fromMillis(millis)
+ updater.setLong(ordinal, micros)
+ case _: TimestampMicros if rebaseDateTime => (updater, ordinal, value) =>
+ val micros = value.asInstanceOf[Long]
+ val rebasedMicros = rebaseJulianToGregorianMicros(micros)
+ updater.setLong(ordinal, rebasedMicros)
++=======
+ case null | _: TimestampMillis => (updater, ordinal, value) =>
+ val millis = value.asInstanceOf[Long]
+ val micros = DateTimeUtils.millisToMicros(millis)
+ updater.setLong(ordinal, timestampRebaseFunc(micros))
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
case _: TimestampMicros => (updater, ordinal, value) =>
val micros = value.asInstanceOf[Long]
- updater.setLong(ordinal, micros)
+ updater.setLong(ordinal, timestampRebaseFunc(micros))
case other => throw new IncompatibleSchemaException(
s"Cannot convert Avro logical type ${other} to Catalyst Timestamp type.")
}
diff --cc external/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala
index dc232168fd2,21c5dec6239..00000000000
--- a/external/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala
+++ b/external/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala
@@@ -155,15 -160,10 +160,22 @@@ class AvroSerializer
case (TimestampType, LONG) => avroType.getLogicalType match {
// For backward compatibility, if the Avro type is Long and it is not logical type
// (the `null` case), output the timestamp value as with millisecond precision.
++<<<<<<< HEAD
+ case null | _: TimestampMillis if rebaseDateTime => (getter, ordinal) =>
+ val micros = getter.getLong(ordinal)
+ val rebasedMicros = rebaseGregorianToJulianMicros(micros)
+ DateTimeUtils.toMillis(rebasedMicros)
+ case null | _: TimestampMillis => (getter, ordinal) =>
+ DateTimeUtils.toMillis(getter.getLong(ordinal))
+ case _: TimestampMicros if rebaseDateTime => (getter, ordinal) =>
+ rebaseGregorianToJulianMicros(getter.getLong(ordinal))
+ case _: TimestampMicros => (getter, ordinal) => getter.getLong(ordinal)
++=======
+ case null | _: TimestampMillis => (getter, ordinal) =>
+ DateTimeUtils.microsToMillis(timestampRebaseFunc(getter.getLong(ordinal)))
+ case _: TimestampMicros => (getter, ordinal) =>
+ timestampRebaseFunc(getter.getLong(ordinal))
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
case other => throw new IncompatibleSchemaException(
s"Cannot convert Catalyst Timestamp type to Avro logical type ${other}")
}
diff --cc sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
index 6c18280ce4d,aeaf884c7d1..00000000000
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
@@@ -2509,57 -2520,71 +2509,83 @@@ object SQLConf
.booleanConf
.createWithDefault(false)
++<<<<<<< HEAD
+ val LEGACY_PARQUET_REBASE_DATETIME_IN_WRITE =
+ buildConf("spark.sql.legacy.parquet.rebaseDateTimeInWrite.enabled")
+ .internal()
+ .doc("When true, rebase dates/timestamps from Proleptic Gregorian calendar " +
+ "to the hybrid calendar (Julian + Gregorian) in write. " +
+ "The rebasing is performed by converting micros/millis/days to " +
+ "a local date/timestamp in the source calendar, interpreting the resulted date/" +
+ "timestamp in the target calendar, and getting the number of micros/millis/days " +
+ "since the epoch 1970-01-01 00:00:00Z.")
- .version("3.0.0")
- .booleanConf
- .createWithDefault(false)
-
- val LEGACY_PARQUET_REBASE_DATETIME_IN_READ =
- buildConf("spark.sql.legacy.parquet.rebaseDateTimeInRead.enabled")
++=======
+ val LEGACY_INTEGER_GROUPING_ID =
+ buildConf("spark.sql.legacy.integerGroupingId")
.internal()
- .doc("When true, rebase dates/timestamps " +
- "from the hybrid calendar to Proleptic Gregorian calendar in read. " +
- "The rebasing is performed by converting micros/millis/days to " +
- "a local date/timestamp in the source calendar, interpreting the resulted date/" +
- "timestamp in the target calendar, and getting the number of micros/millis/days " +
- "since the epoch 1970-01-01 00:00:00Z.")
- .version("3.0.0")
+ .doc("When true, grouping_id() returns int values instead of long values.")
+ .version("3.1.0")
.booleanConf
.createWithDefault(false)
- val LEGACY_AVRO_REBASE_DATETIME_IN_WRITE =
- buildConf("spark.sql.legacy.avro.rebaseDateTimeInWrite.enabled")
+ val LEGACY_PARQUET_REBASE_MODE_IN_WRITE =
+ buildConf("spark.sql.legacy.parquet.datetimeRebaseModeInWrite")
.internal()
- .doc("When true, rebase dates/timestamps from Proleptic Gregorian calendar " +
- "to the hybrid calendar (Julian + Gregorian) in write. " +
- "The rebasing is performed by converting micros/millis/days to " +
- "a local date/timestamp in the source calendar, interpreting the resulted date/" +
- "timestamp in the target calendar, and getting the number of micros/millis/days " +
- "since the epoch 1970-01-01 00:00:00Z.")
+ .doc("When LEGACY, Spark will rebase dates/timestamps from Proleptic Gregorian calendar " +
+ "to the legacy hybrid (Julian + Gregorian) calendar when writing Parquet files. " +
+ "When CORRECTED, Spark will not do rebase and write the dates/timestamps as it is. " +
+ "When EXCEPTION, which is the default, Spark will fail the writing if it sees " +
+ "ancient dates/timestamps that are ambiguous between the two calendars.")
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
.version("3.0.0")
- .booleanConf
- .createWithDefault(false)
+ .stringConf
+ .transform(_.toUpperCase(Locale.ROOT))
+ .checkValues(LegacyBehaviorPolicy.values.map(_.toString))
+ .createWithDefault(LegacyBehaviorPolicy.EXCEPTION.toString)
+
+ val LEGACY_PARQUET_REBASE_MODE_IN_READ =
+ buildConf("spark.sql.legacy.parquet.datetimeRebaseModeInRead")
+ .internal()
+ .doc("When LEGACY, Spark will rebase dates/timestamps from the legacy hybrid (Julian + " +
+ "Gregorian) calendar to Proleptic Gregorian calendar when reading Parquet files. " +
+ "When CORRECTED, Spark will not do rebase and read the dates/timestamps as it is. " +
+ "When EXCEPTION, which is the default, Spark will fail the reading if it sees " +
+ "ancient dates/timestamps that are ambiguous between the two calendars. This config is " +
+ "only effective if the writer info (like Spark, Hive) of the Parquet files is unknown.")
+ .version("3.0.0")
+ .stringConf
+ .transform(_.toUpperCase(Locale.ROOT))
+ .checkValues(LegacyBehaviorPolicy.values.map(_.toString))
+ .createWithDefault(LegacyBehaviorPolicy.EXCEPTION.toString)
- val LEGACY_AVRO_REBASE_DATETIME_IN_READ =
- buildConf("spark.sql.legacy.avro.rebaseDateTimeInRead.enabled")
+ val LEGACY_AVRO_REBASE_MODE_IN_WRITE =
+ buildConf("spark.sql.legacy.avro.datetimeRebaseModeInWrite")
.internal()
- .doc("When true, rebase dates/timestamps " +
- "from the hybrid calendar to Proleptic Gregorian calendar in read. " +
- "The rebasing is performed by converting micros/millis/days to " +
- "a local date/timestamp in the source calendar, interpreting the resulted date/" +
- "timestamp in the target calendar, and getting the number of micros/millis/days " +
- "since the epoch 1970-01-01 00:00:00Z.")
+ .doc("When LEGACY, Spark will rebase dates/timestamps from Proleptic Gregorian calendar " +
+ "to the legacy hybrid (Julian + Gregorian) calendar when writing Avro files. " +
+ "When CORRECTED, Spark will not do rebase and write the dates/timestamps as it is. " +
+ "When EXCEPTION, which is the default, Spark will fail the writing if it sees " +
+ "ancient dates/timestamps that are ambiguous between the two calendars.")
.version("3.0.0")
- .booleanConf
- .createWithDefault(false)
+ .stringConf
+ .transform(_.toUpperCase(Locale.ROOT))
+ .checkValues(LegacyBehaviorPolicy.values.map(_.toString))
+ .createWithDefault(LegacyBehaviorPolicy.EXCEPTION.toString)
+
+ val LEGACY_AVRO_REBASE_MODE_IN_READ =
+ buildConf("spark.sql.legacy.avro.datetimeRebaseModeInRead")
+ .internal()
+ .doc("When LEGACY, Spark will rebase dates/timestamps from the legacy hybrid (Julian + " +
+ "Gregorian) calendar to Proleptic Gregorian calendar when reading Avro files. " +
+ "When CORRECTED, Spark will not do rebase and read the dates/timestamps as it is. " +
+ "When EXCEPTION, which is the default, Spark will fail the reading if it sees " +
+ "ancient dates/timestamps that are ambiguous between the two calendars. This config is " +
+ "only effective if the writer info (like Spark, Hive) of the Avro files is unknown.")
+ .version("3.0.0")
+ .stringConf
+ .transform(_.toUpperCase(Locale.ROOT))
+ .checkValues(LegacyBehaviorPolicy.values.map(_.toString))
+ .createWithDefault(LegacyBehaviorPolicy.EXCEPTION.toString)
/**
* Holds information about keys that have been deprecated.
@@@ -3139,9 -3166,7 +3165,13 @@@ class SQLConf extends Serializable wit
def csvFilterPushDown: Boolean = getConf(CSV_FILTER_PUSHDOWN_ENABLED)
++<<<<<<< HEAD
+ def parquetRebaseDateTimeInReadEnabled: Boolean = {
+ getConf(SQLConf.LEGACY_PARQUET_REBASE_DATETIME_IN_READ)
+ }
++=======
+ def integerGroupingIdEnabled: Boolean = getConf(SQLConf.LEGACY_INTEGER_GROUPING_ID)
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
/** ********************** SQLConf functionality methods ************ */
diff --cc sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
index 11ce11dd721,3e409ab9a50..00000000000
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
@@@ -324,20 -352,20 +352,32 @@@ public class VectorizedColumnReader
}
}
} else if (originalType == OriginalType.TIMESTAMP_MILLIS) {
- if (rebaseDateTime) {
+ if ("CORRECTED".equals(datetimeRebaseMode)) {
for (int i = rowId; i < rowId + num; ++i) {
if (!column.isNullAt(i)) {
++<<<<<<< HEAD
+ long julianMillis = dictionary.decodeToLong(dictionaryIds.getDictId(i));
+ long julianMicros = DateTimeUtils.fromMillis(julianMillis);
+ long gregorianMicros = RebaseDateTime.rebaseJulianToGregorianMicros(julianMicros);
+ column.putLong(i, gregorianMicros);
++=======
+ long gregorianMillis = dictionary.decodeToLong(dictionaryIds.getDictId(i));
+ column.putLong(i, DateTimeUtils.millisToMicros(gregorianMillis));
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
}
}
} else {
+ final boolean failIfRebase = "EXCEPTION".equals(datetimeRebaseMode);
for (int i = rowId; i < rowId + num; ++i) {
if (!column.isNullAt(i)) {
++<<<<<<< HEAD
+ long gregorianMillis = dictionary.decodeToLong(dictionaryIds.getDictId(i));
+ column.putLong(i, DateTimeUtils.fromMillis(gregorianMillis));
++=======
+ long julianMillis = dictionary.decodeToLong(dictionaryIds.getDictId(i));
+ long julianMicros = DateTimeUtils.millisToMicros(julianMillis);
+ column.putLong(i, rebaseMicros(julianMicros, failIfRebase));
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
}
}
}
@@@ -485,27 -514,29 +526,38 @@@
defColumn.readLongs(
num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
} else if (originalType == OriginalType.TIMESTAMP_MICROS) {
- if (rebaseDateTime) {
- defColumn.readLongsWithRebase(
- num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
- } else {
+ if ("CORRECTED".equals(datetimeRebaseMode)) {
defColumn.readLongs(
num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
+ } else {
+ boolean failIfRebase = "EXCEPTION".equals(datetimeRebaseMode);
+ defColumn.readLongsWithRebase(
+ num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn, failIfRebase);
}
} else if (originalType == OriginalType.TIMESTAMP_MILLIS) {
- if (rebaseDateTime) {
+ if ("CORRECTED".equals(datetimeRebaseMode)) {
for (int i = 0; i < num; i++) {
if (defColumn.readInteger() == maxDefLevel) {
++<<<<<<< HEAD
+ long micros = DateTimeUtils.fromMillis(dataColumn.readLong());
+ column.putLong(rowId + i, RebaseDateTime.rebaseJulianToGregorianMicros(micros));
++=======
+ column.putLong(rowId + i, DateTimeUtils.millisToMicros(dataColumn.readLong()));
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
} else {
column.putNull(rowId + i);
}
}
} else {
+ final boolean failIfRebase = "EXCEPTION".equals(datetimeRebaseMode);
for (int i = 0; i < num; i++) {
if (defColumn.readInteger() == maxDefLevel) {
++<<<<<<< HEAD
+ column.putLong(rowId + i, DateTimeUtils.fromMillis(dataColumn.readLong()));
++=======
+ long julianMicros = DateTimeUtils.millisToMicros(dataColumn.readLong());
+ column.putLong(rowId + i, rebaseMicros(julianMicros, failIfRebase));
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
} else {
column.putNull(rowId + i);
}
diff --cc sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
index 08fbca2995c,201ee16faeb..00000000000
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
@@@ -291,19 -289,10 +289,26 @@@ private[parquet] class ParquetRowConver
}
case TimestampType if parquetType.getOriginalType == OriginalType.TIMESTAMP_MILLIS =>
++<<<<<<< HEAD
+ if (rebaseDateTime) {
+ new ParquetPrimitiveConverter(updater) {
+ override def addLong(value: Long): Unit = {
+ val micros = DateTimeUtils.fromMillis(value)
+ val rebased = rebaseJulianToGregorianMicros(micros)
+ updater.setLong(rebased)
+ }
+ }
+ } else {
+ new ParquetPrimitiveConverter(updater) {
+ override def addLong(value: Long): Unit = {
+ updater.setLong(DateTimeUtils.fromMillis(value))
+ }
++=======
+ new ParquetPrimitiveConverter(updater) {
+ override def addLong(value: Long): Unit = {
+ val micros = DateTimeUtils.millisToMicros(value)
+ updater.setLong(timestampRebaseFunc(micros))
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
}
}
diff --cc sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetWriteSupport.scala
index e367b9cc774,6c333671d59..00000000000
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetWriteSupport.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetWriteSupport.scala
@@@ -187,24 -198,15 +198,29 @@@ class ParquetWriteSupport extends Write
buf.order(ByteOrder.LITTLE_ENDIAN).putLong(timeOfDayNanos).putInt(julianDay)
recordConsumer.addBinary(Binary.fromReusedByteArray(timestampBuffer))
- case SQLConf.ParquetOutputTimestampType.TIMESTAMP_MICROS if rebaseDateTime =>
- (row: SpecializedGetters, ordinal: Int) =>
- val rebasedMicros = rebaseGregorianToJulianMicros(row.getLong(ordinal))
- recordConsumer.addLong(rebasedMicros)
-
case SQLConf.ParquetOutputTimestampType.TIMESTAMP_MICROS =>
(row: SpecializedGetters, ordinal: Int) =>
++<<<<<<< HEAD
+ recordConsumer.addLong(row.getLong(ordinal))
+
+ case SQLConf.ParquetOutputTimestampType.TIMESTAMP_MILLIS if rebaseDateTime =>
+ (row: SpecializedGetters, ordinal: Int) =>
+ val rebasedMicros = rebaseGregorianToJulianMicros(row.getLong(ordinal))
+ val millis = DateTimeUtils.toMillis(rebasedMicros)
+ recordConsumer.addLong(millis)
+
+ case SQLConf.ParquetOutputTimestampType.TIMESTAMP_MILLIS =>
+ (row: SpecializedGetters, ordinal: Int) =>
+ val millis = DateTimeUtils.toMillis(row.getLong(ordinal))
++=======
+ val micros = row.getLong(ordinal)
+ recordConsumer.addLong(timestampRebaseFunc(micros))
+
+ case SQLConf.ParquetOutputTimestampType.TIMESTAMP_MILLIS =>
+ (row: SpecializedGetters, ordinal: Int) =>
+ val micros = row.getLong(ordinal)
+ val millis = DateTimeUtils.microsToMillis(timestampRebaseFunc(micros))
++>>>>>>> fd2d55c9919... [SPARK-31405][SQL] Fail by default when reading/writing legacy datetime values from/to Parquet/Avro files
recordConsumer.addLong(millis)
}
```
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