Repository: spark
Updated Branches:
refs/heads/branch-2.4 aff6aedf9 -> e42546259
[SPARK-23549][SQL] Rename config
spark.sql.legacy.compareDateTimestampInTimestamp
## What changes were proposed in this pull request?
See title. Makes our legacy backward compatibility configs more consistent.
## How was this patch tested?
Make sure all references have been updated:
```
> git grep compareDateTimestampInTimestamp
docs/sql-programming-guide.md: - Since Spark 2.4, Spark compares a DATE type
with a TIMESTAMP type after promotes both sides to TIMESTAMP. To set `false` to
`spark.sql.legacy.compareDateTimestampInTimestamp` restores the previous
behavior. This option will be removed in Spark 3.0.
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala:
// if conf.compareDateTimestampInTimestamp is true
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala:
=> if (conf.compareDateTimestampInTimestamp) Some(TimestampType) else
Some(StringType)
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala:
=> if (conf.compareDateTimestampInTimestamp) Some(TimestampType) else
Some(StringType)
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:
buildConf("spark.sql.legacy.compareDateTimestampInTimestamp")
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala: def
compareDateTimestampInTimestamp : Boolean =
getConf(COMPARE_DATE_TIMESTAMP_IN_TIMESTAMP)
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercionSuite.scala:
"spark.sql.legacy.compareDateTimestampInTimestamp" ->
convertToTS.toString) {
```
Closes #22508 from rxin/SPARK-23549.
Authored-by: Reynold Xin <[email protected]>
Signed-off-by: Wenchen Fan <[email protected]>
(cherry picked from commit 411ecc365ea62aef7a29d8764e783e6a58dbb1d5)
Signed-off-by: Wenchen Fan <[email protected]>
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/e4254625
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/e4254625
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/e4254625
Branch: refs/heads/branch-2.4
Commit: e42546259160396d3ddca5d66d0032d18a039df2
Parents: aff6aed
Author: Reynold Xin <[email protected]>
Authored: Fri Sep 21 14:27:14 2018 +0800
Committer: Wenchen Fan <[email protected]>
Committed: Fri Sep 21 14:28:09 2018 +0800
----------------------------------------------------------------------
docs/sql-programming-guide.md | 2 +-
.../org/apache/spark/sql/internal/SQLConf.scala | 35 ++++++++++----------
.../catalyst/analysis/TypeCoercionSuite.scala | 2 +-
3 files changed, 19 insertions(+), 20 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/spark/blob/e4254625/docs/sql-programming-guide.md
----------------------------------------------------------------------
diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md
index 71ca25a..d1c4204 100644
--- a/docs/sql-programming-guide.md
+++ b/docs/sql-programming-guide.md
@@ -1948,7 +1948,7 @@ working with timestamps in `pandas_udf`s to get the best
performance, see
- Since Spark 2.4, writing an empty dataframe to a directory launches at
least one write task, even if physically the dataframe has no partition. This
introduces a small behavior change that for self-describing file formats like
Parquet and Orc, Spark creates a metadata-only file in the target directory
when writing a 0-partition dataframe, so that schema inference can still work
if users read that directory later. The new behavior is more reasonable and
more consistent regarding writing empty dataframe.
- Since Spark 2.4, expression IDs in UDF arguments do not appear in column
names. For example, an column name in Spark 2.4 is not `UDF:f(col0 AS colA#28)`
but ``UDF:f(col0 AS `colA`)``.
- Since Spark 2.4, writing a dataframe with an empty or nested empty schema
using any file formats (parquet, orc, json, text, csv etc.) is not allowed. An
exception is thrown when attempting to write dataframes with empty schema.
- - Since Spark 2.4, Spark compares a DATE type with a TIMESTAMP type after
promotes both sides to TIMESTAMP. To set `false` to
`spark.sql.hive.compareDateTimestampInTimestamp` restores the previous
behavior. This option will be removed in Spark 3.0.
+ - Since Spark 2.4, Spark compares a DATE type with a TIMESTAMP type after
promotes both sides to TIMESTAMP. To set `false` to
`spark.sql.legacy.compareDateTimestampInTimestamp` restores the previous
behavior. This option will be removed in Spark 3.0.
- Since Spark 2.4, creating a managed table with nonempty location is not
allowed. An exception is thrown when attempting to create a managed table with
nonempty location. To set `true` to
`spark.sql.allowCreatingManagedTableUsingNonemptyLocation` restores the
previous behavior. This option will be removed in Spark 3.0.
- Since Spark 2.4, renaming a managed table to existing location is not
allowed. An exception is thrown when attempting to rename a managed table to
existing location.
- Since Spark 2.4, the type coercion rules can automatically promote the
argument types of the variadic SQL functions (e.g., IN/COALESCE) to the widest
common type, no matter how the input arguments order. In prior Spark versions,
the promotion could fail in some specific orders (e.g., TimestampType,
IntegerType and StringType) and throw an exception.
http://git-wip-us.apache.org/repos/asf/spark/blob/e4254625/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
----------------------------------------------------------------------
diff --git
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
index 4b8ce74..610f11b 100644
--- 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
@@ -557,16 +557,6 @@ object SQLConf {
.checkValues(HiveCaseSensitiveInferenceMode.values.map(_.toString))
.createWithDefault(HiveCaseSensitiveInferenceMode.INFER_AND_SAVE.toString)
- val TYPECOERCION_COMPARE_DATE_TIMESTAMP_IN_TIMESTAMP =
- buildConf("spark.sql.typeCoercion.compareDateTimestampInTimestamp")
- .internal()
- .doc("When true (default), compare Date with Timestamp after converting
both sides to " +
- "Timestamp. This behavior is compatible with Hive 2.2 or later. See
HIVE-15236. " +
- "When false, restore the behavior prior to Spark 2.4. Compare Date
with Timestamp after " +
- "converting both sides to string. This config will be removed in spark
3.0")
- .booleanConf
- .createWithDefault(true)
-
val OPTIMIZER_METADATA_ONLY = buildConf("spark.sql.optimizer.metadataOnly")
.doc("When true, enable the metadata-only query optimization that use the
table's metadata " +
"to produce the partition columns instead of table scans. It applies
when all the columns " +
@@ -1456,12 +1446,6 @@ object SQLConf {
.booleanConf
.createWithDefault(true)
- val LEGACY_SIZE_OF_NULL = buildConf("spark.sql.legacy.sizeOfNull")
- .doc("If it is set to true, size of null returns -1. This behavior was
inherited from Hive. " +
- "The size function returns null for null input if the flag is disabled.")
- .booleanConf
- .createWithDefault(true)
-
val REPL_EAGER_EVAL_ENABLED = buildConf("spark.sql.repl.eagerEval.enabled")
.doc("Enables eager evaluation or not. When true, the top K rows of
Dataset will be " +
"displayed if and only if the REPL supports the eager evaluation.
Currently, the " +
@@ -1511,6 +1495,22 @@ object SQLConf {
.checkValues((1 to 9).toSet + Deflater.DEFAULT_COMPRESSION)
.createWithDefault(Deflater.DEFAULT_COMPRESSION)
+ val COMPARE_DATE_TIMESTAMP_IN_TIMESTAMP =
+ buildConf("spark.sql.legacy.compareDateTimestampInTimestamp")
+ .internal()
+ .doc("When true (default), compare Date with Timestamp after converting
both sides to " +
+ "Timestamp. This behavior is compatible with Hive 2.2 or later. See
HIVE-15236. " +
+ "When false, restore the behavior prior to Spark 2.4. Compare Date
with Timestamp after " +
+ "converting both sides to string. This config will be removed in Spark
3.0.")
+ .booleanConf
+ .createWithDefault(true)
+
+ val LEGACY_SIZE_OF_NULL = buildConf("spark.sql.legacy.sizeOfNull")
+ .doc("If it is set to true, size of null returns -1. This behavior was
inherited from Hive. " +
+ "The size function returns null for null input if the flag is disabled.")
+ .booleanConf
+ .createWithDefault(true)
+
val LEGACY_REPLACE_DATABRICKS_SPARK_AVRO_ENABLED =
buildConf("spark.sql.legacy.replaceDatabricksSparkAvro.enabled")
.doc("If it is set to true, the data source provider
com.databricks.spark.avro is mapped " +
@@ -1660,8 +1660,7 @@ class SQLConf extends Serializable with Logging {
def caseSensitiveInferenceMode: HiveCaseSensitiveInferenceMode.Value =
HiveCaseSensitiveInferenceMode.withName(getConf(HIVE_CASE_SENSITIVE_INFERENCE))
- def compareDateTimestampInTimestamp : Boolean =
- getConf(TYPECOERCION_COMPARE_DATE_TIMESTAMP_IN_TIMESTAMP)
+ def compareDateTimestampInTimestamp : Boolean =
getConf(COMPARE_DATE_TIMESTAMP_IN_TIMESTAMP)
def gatherFastStats: Boolean = getConf(GATHER_FASTSTAT)
http://git-wip-us.apache.org/repos/asf/spark/blob/e4254625/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercionSuite.scala
----------------------------------------------------------------------
diff --git
a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercionSuite.scala
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercionSuite.scala
index 1602f4d..0594673 100644
---
a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercionSuite.scala
+++
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercionSuite.scala
@@ -1459,7 +1459,7 @@ class TypeCoercionSuite extends AnalysisTest {
DoubleType)))
Seq(true, false).foreach { convertToTS =>
withSQLConf(
- "spark.sql.typeCoercion.compareDateTimestampInTimestamp" ->
convertToTS.toString) {
+ "spark.sql.legacy.compareDateTimestampInTimestamp" ->
convertToTS.toString) {
val date0301 = Literal(java.sql.Date.valueOf("2017-03-01"))
val timestamp0301000000 = Literal(Timestamp.valueOf("2017-03-01
00:00:00"))
val timestamp0301000001 = Literal(Timestamp.valueOf("2017-03-01
00:00:01"))
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