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[GitHub] [spark] SparkQA commented on pull request #28645: [SPARK-31826][SQL] Support composed type of case class for typed Scala UDF
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[GitHub] [spark] maropu commented on pull request #28527: [SPARK-31709][SQL] Proper base path for database/table location when it is a relative path
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[GitHub] [spark] maropu commented on pull request #28527: [SPARK-31709][SQL] Proper base path for database/table location when it is a relative path
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[GitHub] [spark] cloud-fan commented on pull request #28650: [SPARK-31830][SQL] Consistent error handling for datetime formatting and parsing functions
cloud-fan commented on pull request #28650: URL: https://github.com/apache/spark/pull/28650#issuecomment-635808253 Since this PR is for master only, let's fix the `format()` first, in case this PR introduces conflicts. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins commented on pull request #28527: [SPARK-31709][SQL] Proper base path for database/table location when it is a relative path
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[GitHub] [spark] cloud-fan commented on pull request #28626: [SPARK-28481][SQL] More expressions should extend NullIntolerant
cloud-fan commented on pull request #28626: URL: https://github.com/apache/spark/pull/28626#issuecomment-635810298 thanks, merging to master! This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] cloud-fan closed pull request #28626: [SPARK-28481][SQL] More expressions should extend NullIntolerant
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[GitHub] [spark] huaxingao commented on pull request #28672: [SPARK-31866][SQL][DOCS] Add Coalesce/Repartition/Repartition_By_Range Hints to SQL Reference
huaxingao commented on pull request #28672: URL: https://github.com/apache/spark/pull/28672#issuecomment-635811122 Yes, it's for 3.0. I created jira SPARK-31866. @maropu This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on pull request #28672: [SPARK-31866][SQL][DOCS] Add Coalesce/Repartition/Repartition_By_Range Hints to SQL Reference
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[GitHub] [spark] viirya commented on a change in pull request #28648: [SPARK-31788][CORE][DSTREAM][PYTHON] Recover the support of union for different types of RDD and DStreams
viirya commented on a change in pull request #28648: URL: https://github.com/apache/spark/pull/28648#discussion_r432297967 ## File path: python/pyspark/context.py ## @@ -864,8 +865,21 @@ def union(self, rdds): first_jrdd_deserializer = rdds[0]._jrdd_deserializer if any(x._jrdd_deserializer != first_jrdd_deserializer for x in rdds): rdds = [x._reserialize() for x in rdds] -cls = SparkContext._jvm.org.apache.spark.api.java.JavaRDD -jrdds = SparkContext._gateway.new_array(cls, len(rdds)) +gw = SparkContext._gateway +jvm = SparkContext._jvm +jrdd_cls = jvm.org.apache.spark.api.java.JavaRDD +jpair_rdd_cls = jvm.org.apache.spark.api.java.JavaPairRDD +jdouble_rdd_cls = jvm.org.apache.spark.api.java.JavaDoubleRDD +if is_instance_of(gw, rdds[0]._jrdd, jrdd_cls): +cls = jrdd_cls +elif is_instance_of(gw, rdds[0]._jrdd, jpair_rdd_cls): +cls = jpair_rdd_cls +elif is_instance_of(gw, rdds[0]._jrdd, jdouble_rdd_cls): +cls = jdouble_rdd_cls +else: +cls_name = rdds[0]._jrdd.getClass().getCanonicalName() +raise TypeError("Unsupported Java DStream class %s" % cls_name) +jrdds = gw.new_array(cls, len(rdds)) Review comment: Why we say Java DStream class here? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] SparkQA commented on pull request #28647: [SPARK-31828][SQL] Retain table properties at CreateTableLikeCommand
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[GitHub] [spark] ulysses-you commented on a change in pull request #28647: [SPARK-31828][SQL] Retain table properties at CreateTableLikeCommand
ulysses-you commented on a change in pull request #28647: URL: https://github.com/apache/spark/pull/28647#discussion_r432308450 ## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/command/tables.scala ## @@ -115,6 +116,15 @@ case class CreateTableLikeCommand( CatalogTableType.EXTERNAL } +val newProperties = sourceTableDesc.tableType match { + case VIEW => +// For view, we just use new properties +properties Review comment: Keep view behavior as before. Hive also does not copy view properties. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] SparkQA commented on pull request #28593: [SPARK-31710][SQL] Fail casting numeric to timestamp by default
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[GitHub] [spark] maropu commented on a change in pull request #28672: [SPARK-31866][SQL][DOCS] Add COALESCE/REPARTITION/REPARTITION_BY_RANGE Hints to SQL Reference
maropu commented on a change in pull request #28672: URL: https://github.com/apache/spark/pull/28672#discussion_r432308677 ## File path: docs/sql-ref-syntax-qry-select-hints.md ## @@ -21,14 +21,69 @@ license: | ### Description -Join Hints allow users to suggest the join strategy that Spark should use. Prior to Spark 3.0, only the `BROADCAST` Join Hint was supported. `MERGE`, `SHUFFLE_HASH` and `SHUFFLE_REPLICATE_NL` Joint Hints support was added in 3.0. When different join strategy hints are specified on both sides of a join, Spark prioritizes hints in the following order: `BROADCAST` over `MERGE` over `SHUFFLE_HASH` over `SHUFFLE_REPLICATE_NL`. When both sides are specified with the `BROADCAST` hint or the `SHUFFLE_HASH` hint, Spark will pick the build side based on the join type and the sizes of the relations. Since a given strategy may not support all join types, Spark is not guaranteed to use the join strategy suggested by the hint. +Hints give users a way to suggest how Spark SQL to use specific approaches to generate its execution plan. ### Syntax ```sql -/*+ join_hint [ , ... ] */ +/*+ hint [ , ... ] */ ``` +### Partitioning Hints + +`COALESCE`/`REPARTITION`/`REPARTITION_BY_RANGE` hints have functionalities equivalent to those of the +`Dataset` `coalesce`/`repartition`/`repartitionByRange` APIs. The `COALESCE` hint can be used to reduce +the number of partitions to the specified number of partitions. The `REPARTITION`/`REPARTITION_BY_RANGE` +hint can be used to repartition to the specified number of partitions using the specified partitioning expressions. +The `COALESCE` hint takes a partition number as a +parameter. The `REPARTITION` hint takes a partition number, column names, or both as parameters. +The `REPARTITION_BY_RANGE` hint takes column names and an optional partition number as parameters. +These hints give users a way to tune performance and control the number of output files in Spark SQL. + +### Examples +```sql +SELECT /*+ COALESCE(3) */ * FROM t; + +EXPLAIN SELECT /*+ COALESCE(3) */ * FROM t; +== Physical Plan == +Coalesce 3 ++- *(1) ColumnarToRow + +- FileScan parquet default.t[name#5,c#6] Batched: true, DataFilters: [], Format: Parquet, + Location: CatalogFileIndex[file:/spark/spark-warehouse/t], PartitionFilters: [], + PushedFilters: [], ReadSchema: struct + +SELECT /*+ REPARTITION(3) */ * FROM t; + +SELECT /*+ REPARTITION(c) */ * FROM t; + +SELECT /*+ REPARTITION(3, c) */ * FROM t; + +EXPLAIN SELECT /*+ REPARTITION(3, c) */ * FROM t; +== Physical Plan == +Exchange hashpartitioning(c#6, 3), false, [id=#148] ++- *(1) ColumnarToRow + +- FileScan parquet default.t[name#5,c#6] Batched: true, DataFilters: [], Format: Parquet, + Location: CatalogFileIndex[file:/spark/spark-warehouse/t], PartitionFilters: [], + PushedFilters: [], ReadSchema: struct + +SELECT /*+ REPARTITION_BY_RANGE(c) */ * FROM t; + +SELECT /*+ REPARTITION_BY_RANGE(3, c) */ * FROM t; + +EXPLAIN SELECT /*+ REPARTITION_BY_RANGE(3, c) */ * FROM t; +== Physical Plan == +Exchange rangepartitioning(c#6 ASC NULLS FIRST, 3), false, [id=#167] ++- *(1) ColumnarToRow + +- FileScan parquet default.t[name#5,c#6] Batched: true, DataFilters: [], Format: Parquet, + Location: CatalogFileIndex[file:/spark/spark-warehouse/t], PartitionFilters: [], + PushedFilters: [], ReadSchema: struct +``` + + +### Join Hints + +Join Hints allow users to suggest the join strategy that Spark should use. Prior to Spark 3.0, only the `BROADCAST` Join Hint was supported. `MERGE`, `SHUFFLE_HASH` and `SHUFFLE_REPLICATE_NL` Joint Hints support was added in 3.0. When different join strategy hints are specified on both sides of a join, Spark prioritizes hints in the following order: `BROADCAST` over `MERGE` over `SHUFFLE_HASH` over `SHUFFLE_REPLICATE_NL`. When both sides are specified with the `BROADCAST` hint or the `SHUFFLE_HASH` hint, Spark will pick the build side based on the join type and the sizes of the relations. Since a given strategy may not support all join types, Spark is not guaranteed to use the join strategy suggested by the hint. Review comment: `Hints` -> `hints`? ## File path: docs/sql-ref-syntax-qry-select-hints.md ## @@ -21,14 +21,69 @@ license: | ### Description -Join Hints allow users to suggest the join strategy that Spark should use. Prior to Spark 3.0, only the `BROADCAST` Join Hint was supported. `MERGE`, `SHUFFLE_HASH` and `SHUFFLE_REPLICATE_NL` Joint Hints support was added in 3.0. When different join strategy hints are specified on both sides of a join, Spark prioritizes hints in the following order: `BROADCAST` over `MERGE` over `SHUFFLE_HASH` over `SHUFFLE_REPLICATE_NL`. When both sides are specified with the `BROADCAST` hint or the `SHUFFLE_HASH` hint, Spark will pick the build side based on the join type and the sizes of the relations. Since a given strategy may not support all join types, Sp
[GitHub] [spark] maropu commented on a change in pull request #28672: [SPARK-31866][SQL][DOCS] Add COALESCE/REPARTITION/REPARTITION_BY_RANGE Hints to SQL Reference
maropu commented on a change in pull request #28672: URL: https://github.com/apache/spark/pull/28672#discussion_r432314600 ## File path: docs/sql-ref-syntax-qry-select-hints.md ## @@ -21,14 +21,69 @@ license: | ### Description -Join Hints allow users to suggest the join strategy that Spark should use. Prior to Spark 3.0, only the `BROADCAST` Join Hint was supported. `MERGE`, `SHUFFLE_HASH` and `SHUFFLE_REPLICATE_NL` Joint Hints support was added in 3.0. When different join strategy hints are specified on both sides of a join, Spark prioritizes hints in the following order: `BROADCAST` over `MERGE` over `SHUFFLE_HASH` over `SHUFFLE_REPLICATE_NL`. When both sides are specified with the `BROADCAST` hint or the `SHUFFLE_HASH` hint, Spark will pick the build side based on the join type and the sizes of the relations. Since a given strategy may not support all join types, Spark is not guaranteed to use the join strategy suggested by the hint. +Hints give users a way to suggest how Spark SQL to use specific approaches to generate its execution plan. ### Syntax ```sql -/*+ join_hint [ , ... ] */ +/*+ hint [ , ... ] */ ``` +### Partitioning Hints + +`COALESCE`/`REPARTITION`/`REPARTITION_BY_RANGE` hints have functionalities equivalent to those of the Review comment: Also, could you add links to the Dataset APIs if we describe them here? https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.Dataset This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins commented on pull request #28645: [SPARK-31826][SQL] Support composed type of case class for typed Scala UDF
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[GitHub] [spark] maropu commented on a change in pull request #28672: [SPARK-31866][SQL][DOCS] Add COALESCE/REPARTITION/REPARTITION_BY_RANGE Hints to SQL Reference
maropu commented on a change in pull request #28672: URL: https://github.com/apache/spark/pull/28672#discussion_r432315161 ## File path: docs/sql-ref-syntax-qry-select-hints.md ## @@ -21,14 +21,69 @@ license: | ### Description -Join Hints allow users to suggest the join strategy that Spark should use. Prior to Spark 3.0, only the `BROADCAST` Join Hint was supported. `MERGE`, `SHUFFLE_HASH` and `SHUFFLE_REPLICATE_NL` Joint Hints support was added in 3.0. When different join strategy hints are specified on both sides of a join, Spark prioritizes hints in the following order: `BROADCAST` over `MERGE` over `SHUFFLE_HASH` over `SHUFFLE_REPLICATE_NL`. When both sides are specified with the `BROADCAST` hint or the `SHUFFLE_HASH` hint, Spark will pick the build side based on the join type and the sizes of the relations. Since a given strategy may not support all join types, Spark is not guaranteed to use the join strategy suggested by the hint. +Hints give users a way to suggest how Spark SQL to use specific approaches to generate its execution plan. ### Syntax ```sql -/*+ join_hint [ , ... ] */ +/*+ hint [ , ... ] */ ``` +### Partitioning Hints + +`COALESCE`/`REPARTITION`/`REPARTITION_BY_RANGE` hints have functionalities equivalent to those of the +`Dataset` `coalesce`/`repartition`/`repartitionByRange` APIs. The `COALESCE` hint can be used to reduce +the number of partitions to the specified number of partitions. The `REPARTITION`/`REPARTITION_BY_RANGE` +hint can be used to repartition to the specified number of partitions using the specified partitioning expressions. +The `COALESCE` hint takes a partition number as a +parameter. The `REPARTITION` hint takes a partition number, column names, or both as parameters. +The `REPARTITION_BY_RANGE` hint takes column names and an optional partition number as parameters. +These hints give users a way to tune performance and control the number of output files in Spark SQL. + +### Examples +```sql +SELECT /*+ COALESCE(3) */ * FROM t; + +EXPLAIN SELECT /*+ COALESCE(3) */ * FROM t; +== Physical Plan == +Coalesce 3 ++- *(1) ColumnarToRow + +- FileScan parquet default.t[name#5,c#6] Batched: true, DataFilters: [], Format: Parquet, + Location: CatalogFileIndex[file:/spark/spark-warehouse/t], PartitionFilters: [], + PushedFilters: [], ReadSchema: struct + +SELECT /*+ REPARTITION(3) */ * FROM t; Review comment: One more comment; probably, the join hint section should have the same format for the examples. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on pull request #28645: [SPARK-31826][SQL] Support composed type of case class for typed Scala UDF
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[GitHub] [spark] SparkQA removed a comment on pull request #28645: [SPARK-31826][SQL] Support composed type of case class for typed Scala UDF
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[GitHub] [spark] SparkQA commented on pull request #28656: [SPARK-31837][CORE] Shift to the new highest locality level if there is when recomputeLocality
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[GitHub] [spark] AmplabJenkins removed a comment on pull request #28645: [SPARK-31826][SQL] Support composed type of case class for typed Scala UDF
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[GitHub] [spark] JkSelf commented on a change in pull request #28669: [SPARK-31864][SQL] Adjust AQE skew join trigger condition
JkSelf commented on a change in pull request #28669: URL: https://github.com/apache/spark/pull/28669#discussion_r432316209 ## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeSkewedJoin.scala ## @@ -164,15 +164,15 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends Rule[SparkPlan] { assert(left.partitionsWithSizes.length == right.partitionsWithSizes.length) val numPartitions = left.partitionsWithSizes.length // We use the median size of the original shuffle partitions to detect skewed partitions. Review comment: We may also need to adjust the comment here. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins commented on pull request #28656: [SPARK-31837][CORE] Shift to the new highest locality level if there is when recomputeLocality
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[GitHub] [spark] AmplabJenkins removed a comment on pull request #28656: [SPARK-31837][CORE] Shift to the new highest locality level if there is when recomputeLocality
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[GitHub] [spark] JkSelf commented on pull request #28669: [SPARK-31864][SQL] Adjust AQE skew join trigger condition
JkSelf commented on pull request #28669: URL: https://github.com/apache/spark/pull/28669#issuecomment-635823877 Good improvement. Except one small comment. LGTM. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] Ngone51 commented on a change in pull request #28656: [SPARK-31837][CORE] Shift to the new highest locality level if there is when recomputeLocality
Ngone51 commented on a change in pull request #28656: URL: https://github.com/apache/spark/pull/28656#discussion_r432318441 ## File path: core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala ## @@ -1107,10 +1107,19 @@ private[spark] class TaskSetManager( def recomputeLocality(): Unit = { // A zombie TaskSetManager may reach here while executorLost happens if (isZombie) return +val previousLocalityIndex = currentLocalityIndex val previousLocalityLevel = myLocalityLevels(currentLocalityIndex) +val previousMyLocalityLevels = myLocalityLevels myLocalityLevels = computeValidLocalityLevels() localityWaits = myLocalityLevels.map(getLocalityWait) currentLocalityIndex = getLocalityIndex(previousLocalityLevel) +if (currentLocalityIndex > previousLocalityIndex) { + // SPARK-31837: If the new level is more local, shift to the new most local locality + // level in terms of better data locality. For example, say the previous locality + // levels are [PROCESS, NODE, ANY] and current level is ANY. After recompute, the + // locality levels are [PROCESS, NODE, RACK, ANY]. Then, we'll shift to RACK level. + currentLocalityIndex = getLocalityIndex(myLocalityLevels.diff(previousMyLocalityLevels).head) Review comment: Hi all, there's a defect in the previous implement(always reset `currentLocalityIndex` to 0). Think about such a case, say we have locality levels [PROCESS, NODE, ANY] and current locality level is ANY. After recompute, we might have locality levels [PROCESS, NODE, RACK, ANY]. In this case, I think we'd better shit to RACK level instead of PROCESS level, since the TaskSetManager has been already delayed for a while on known levels(PROCESS, NODE). So with this update, I think it could also ease our concern on the possible perf regression introduced by aggressive locality level resetting. @bmarcott @tgravescs @cloud-fan This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on pull request #28661: [SPARK-31849][PYTHON][SQL] Make PySpark SQL exceptions more Pythonic
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #28648: [SPARK-31788][CORE][DSTREAM][PYTHON] Recover the support of union for different types of RDD and DStreams
HyukjinKwon commented on a change in pull request #28648: URL: https://github.com/apache/spark/pull/28648#discussion_r432320301 ## File path: python/pyspark/context.py ## @@ -864,8 +865,21 @@ def union(self, rdds): first_jrdd_deserializer = rdds[0]._jrdd_deserializer if any(x._jrdd_deserializer != first_jrdd_deserializer for x in rdds): rdds = [x._reserialize() for x in rdds] -cls = SparkContext._jvm.org.apache.spark.api.java.JavaRDD -jrdds = SparkContext._gateway.new_array(cls, len(rdds)) +gw = SparkContext._gateway +jvm = SparkContext._jvm +jrdd_cls = jvm.org.apache.spark.api.java.JavaRDD +jpair_rdd_cls = jvm.org.apache.spark.api.java.JavaPairRDD +jdouble_rdd_cls = jvm.org.apache.spark.api.java.JavaDoubleRDD +if is_instance_of(gw, rdds[0]._jrdd, jrdd_cls): +cls = jrdd_cls +elif is_instance_of(gw, rdds[0]._jrdd, jpair_rdd_cls): +cls = jpair_rdd_cls +elif is_instance_of(gw, rdds[0]._jrdd, jdouble_rdd_cls): +cls = jdouble_rdd_cls +else: +cls_name = rdds[0]._jrdd.getClass().getCanonicalName() +raise TypeError("Unsupported Java DStream class %s" % cls_name) +jrdds = gw.new_array(cls, len(rdds)) Review comment: Thanks for pointing this out. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on pull request #28648: [SPARK-31788][CORE][DSTREAM][PYTHON] Recover the support of union for different types of RDD and DStreams
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[GitHub] [spark] AmplabJenkins commented on pull request #28648: [SPARK-31788][CORE][DSTREAM][PYTHON] Recover the support of union for different types of RDD and DStreams
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[GitHub] [spark] maropu commented on a change in pull request #18323: [SPARK-21117][SQL] Built-in SQL Function Support - WIDTH_BUCKET
maropu commented on a change in pull request #18323: URL: https://github.com/apache/spark/pull/18323#discussion_r432325959 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala ## @@ -1319,3 +1319,123 @@ case class BRound(child: Expression, scale: Expression) with Serializable with ImplicitCastInputTypes { def this(child: Expression) = this(child, Literal(0)) } + +/** + * Returns the bucket number into which + * the value of this expression would fall after being evaluated. + * + * @param expr is the expression for which the histogram is being created + * @param minValue is an expression that resolves + * to the minimum end point of the acceptable range for expr + * @param maxValue is an expression that resolves + * to the maximum end point of the acceptable range for expr + * @param numBucket is an expression that resolves to + * a constant indicating the number of buckets + */ +// scalastyle:off line.size.limit +@ExpressionDescription( + usage = "_FUNC_(expr, min_value, max_value, num_bucket) - Returns the `bucket` to which operand would be assigned in an equidepth histogram with `num_bucket` buckets, in the range `min_value` to `max_value`.", + extended = """ +Examples: + > SELECT _FUNC_(5.35, 0.024, 10.06, 5); + 3 + """) +// scalastyle:on line.size.limit +case class WidthBucket( + expr: Expression, + minValue: Expression, + maxValue: Expression, + numBucket: Expression) extends Expression with ImplicitCastInputTypes { Review comment: Cloud we do `WidthBucket (...) extends QuaternaryExpression with ImplicitCastInputTypes with CodegenFallback` for simplicity? If we need the codegen support, I think its okay to do so in follow-up. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] maropu commented on a change in pull request #18323: [SPARK-21117][SQL] Built-in SQL Function Support - WIDTH_BUCKET
maropu commented on a change in pull request #18323: URL: https://github.com/apache/spark/pull/18323#discussion_r432326338 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala ## @@ -1319,3 +1319,123 @@ case class BRound(child: Expression, scale: Expression) with Serializable with ImplicitCastInputTypes { def this(child: Expression) = this(child, Literal(0)) } + +/** + * Returns the bucket number into which + * the value of this expression would fall after being evaluated. Review comment: nit format: ``` /** * Returns the bucket number into which the value of this expression would fall * after being evaluated. * ``` This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] maropu commented on a change in pull request #18323: [SPARK-21117][SQL] Built-in SQL Function Support - WIDTH_BUCKET
maropu commented on a change in pull request #18323: URL: https://github.com/apache/spark/pull/18323#discussion_r432326868 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala ## @@ -1319,3 +1319,123 @@ case class BRound(child: Expression, scale: Expression) with Serializable with ImplicitCastInputTypes { def this(child: Expression) = this(child, Literal(0)) } + +/** + * Returns the bucket number into which + * the value of this expression would fall after being evaluated. + * + * @param expr is the expression for which the histogram is being created + * @param minValue is an expression that resolves + * to the minimum end point of the acceptable range for expr + * @param maxValue is an expression that resolves + * to the maximum end point of the acceptable range for expr + * @param numBucket is an expression that resolves to + * a constant indicating the number of buckets + */ +// scalastyle:off line.size.limit +@ExpressionDescription( + usage = "_FUNC_(expr, min_value, max_value, num_bucket) - Returns the `bucket` to which operand would be assigned in an equidepth histogram with `num_bucket` buckets, in the range `min_value` to `max_value`.", + extended = """ Review comment: `extended` -> `examples`. Also, plz add a `since` tag. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] juliuszsompolski commented on a change in pull request #28671: [SPARK-31859][SPARK-31861][SPARK-31863] Fix Thriftserver session timezone issues
juliuszsompolski commented on a change in pull request #28671: URL: https://github.com/apache/spark/pull/28671#discussion_r432327826 ## File path: sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkOperationUtils.scala ## @@ -0,0 +1,78 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + *http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.hive.thriftserver + +import org.apache.hive.service.cli.session.HiveSession + +import org.apache.spark.SparkContext +import org.apache.spark.sql.{SparkSession, SQLContext} +import org.apache.spark.sql.catalyst.catalog.CatalogTableType +import org.apache.spark.sql.catalyst.catalog.CatalogTableType.{EXTERNAL, MANAGED, VIEW} +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.util.Utils + +/** + * Utils for Spark operations. + */ +private[hive] trait SparkOperationUtils { Review comment: Nice. Do you think I could roll the close() function like that as well in this PR? It's repetitive across all operations, only SparkExecuteStatementOperation needs it slightly different. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] maropu commented on a change in pull request #18323: [SPARK-21117][SQL] Built-in SQL Function Support - WIDTH_BUCKET
maropu commented on a change in pull request #18323: URL: https://github.com/apache/spark/pull/18323#discussion_r432329283 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala ## @@ -1319,3 +1319,123 @@ case class BRound(child: Expression, scale: Expression) with Serializable with ImplicitCastInputTypes { def this(child: Expression) = this(child, Literal(0)) } + +/** + * Returns the bucket number into which + * the value of this expression would fall after being evaluated. + * + * @param expr is the expression for which the histogram is being created + * @param minValue is an expression that resolves + * to the minimum end point of the acceptable range for expr + * @param maxValue is an expression that resolves + * to the maximum end point of the acceptable range for expr + * @param numBucket is an expression that resolves to + * a constant indicating the number of buckets + */ +// scalastyle:off line.size.limit +@ExpressionDescription( + usage = "_FUNC_(expr, min_value, max_value, num_bucket) - Returns the `bucket` to which operand would be assigned in an equidepth histogram with `num_bucket` buckets, in the range `min_value` to `max_value`.", + extended = """ +Examples: + > SELECT _FUNC_(5.35, 0.024, 10.06, 5); + 3 + """) +// scalastyle:on line.size.limit +case class WidthBucket( + expr: Expression, + minValue: Expression, + maxValue: Expression, + numBucket: Expression) extends Expression with ImplicitCastInputTypes { + + override def children: Seq[Expression] = Seq(expr, minValue, maxValue, numBucket) + override def foldable: Boolean = children.drop(1).forall(_.foldable) + override def inputTypes: Seq[AbstractDataType] = Seq(DoubleType, DoubleType, DoubleType, LongType) + override def dataType: DataType = LongType + override def nullable: Boolean = true + + private lazy val _minValue: Any = minValue.eval() + private lazy val minValueV = _minValue.asInstanceOf[Double] + + private lazy val _maxValue: Any = maxValue.eval() + private lazy val maxValueV = _maxValue.asInstanceOf[Double] + + private lazy val _numBucket: Any = numBucket.eval() + private lazy val numBucketV = _numBucket.asInstanceOf[Long] + + private val errMsg = "The argument [%d] of WIDTH_BUCKET function is NULL or invalid." + + override def eval(input: InternalRow): Any = { + +if (foldable) { + if (_minValue == null) { +throw new RuntimeException(errMsg.format(2)) + } else if (_maxValue == null) { +throw new RuntimeException(errMsg.format(3)) + } else if (_numBucket == null || numBucketV <= 0) { +throw new RuntimeException(errMsg.format(4)) + } else { +val exprV = expr.eval(input) +if (exprV == null) { + null +} else { + MathUtils.widthBucket(exprV.asInstanceOf[Double], minValueV, maxValueV, numBucketV) +} + } +} else { + val evals = children.map(_.eval(input)) + val invalid = evals.zipWithIndex.filter { case (e, i) => +(i > 0 && e == null) || (i == 3 && e.asInstanceOf[Long] <= 0) + } + if (invalid.nonEmpty) { +invalid.foreach(l => throw new RuntimeException(errMsg.format(l._2 + 1))) + } else if (evals(0) == null) { +null + } else { +MathUtils.widthBucket( Review comment: `MathUtils.widthBucket` is used only for this new expr now? If so, could we move the method to this expr? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] yaooqinn opened a new pull request #28673: [SPARK-31867][SQL] Fix silent data change for datetime formatting
yaooqinn opened a new pull request #28673: URL: https://github.com/apache/spark/pull/28673 ### What changes were proposed in this pull request? the new datetime formatter introduces silent data change like, ```sql spark-sql> select from_unixtime(1, 'yyy-MM-dd'); NULL spark-sql> set spark.sql.legacy.timeParserPolicy=legacy; spark.sql.legacy.timeParserPolicylegacy spark-sql> select from_unixtime(1, 'yyy-MM-dd'); 0001970-01-01 spark-sql> ``` For patterns that support `SignStyle.EXCEEDS_PAD`, e.g. `y..y`(len >=4), when using the `NumberPrinterParser` to format it ```java switch (signStyle) { case EXCEEDS_PAD: if (minWidth < 19 && value >= EXCEED_POINTS[minWidth]) { buf.append(decimalStyle.getPositiveSign()); } break; ``` the `minWidth` == `len(y..y)` the `EXCEED_POINTS` is ```java /** * Array of 10 to the power of n. */ static final long[] EXCEED_POINTS = new long[] { 0L, 10L, 100L, 1000L, 1L, 10L, 100L, 1000L, 1L, 10L, 100L, }; ``` So when the `len(y..y)` is greater than 10, ` ArrayIndexOutOfBoundsException` will be raised. And at the caller side, for `from_unixtime`, the exception will be suppressed and silent data change occurs. for `date_format`, the `ArrayIndexOutOfBoundsException` will continue. In this PR, for `EXCEPTION` mode, we wrapped exceptions from the new formatter during formatting to `SparkUpgradeException` for end-users to make proper decisions. ### Why are the changes needed? fix silent data change. ### Does this PR introduce _any_ user-facing change? Yes, SparkUpgradeException will take place of `null` result when something is wrong during new formatter's formatting phase. ### How was this patch tested? add unit tests, the `sql/core/src/test/resources/sql-tests/results/datetime-corrected.sql.out` is added for different behaviors from the caller sides. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on pull request #28673: [SPARK-31867][SQL] Fix silent data change for datetime formatting
SparkQA commented on pull request #28673: URL: https://github.com/apache/spark/pull/28673#issuecomment-635842893 **[Test build #123276 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/123276/testReport)** for PR 28673 at commit [`fc91f2d`](https://github.com/apache/spark/commit/fc91f2d7a79561471077dabddf8b0b0e028d537f). This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] maropu commented on a change in pull request #18323: [SPARK-21117][SQL] Built-in SQL Function Support - WIDTH_BUCKET
maropu commented on a change in pull request #18323: URL: https://github.com/apache/spark/pull/18323#discussion_r432326338 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala ## @@ -1319,3 +1319,123 @@ case class BRound(child: Expression, scale: Expression) with Serializable with ImplicitCastInputTypes { def this(child: Expression) = this(child, Literal(0)) } + +/** + * Returns the bucket number into which + * the value of this expression would fall after being evaluated. Review comment: nit: how about the format and the rephrasing below? ``` /** * Returns the bucket number into which the value of this expression would fall * after being evaluated. * * @param expr is the expression to compute a bucket number in the histogram * @param minValue is the minimum value of the histogram * @param maxValue is the maximum value of the histogram * @param numBucket is the number of buckets */ ``` This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins commented on pull request #28673: [SPARK-31867][SQL] Fix silent data change for datetime formatting
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[GitHub] [spark] yaooqinn commented on pull request #28673: [SPARK-31867][SQL] Fix silent data change for datetime formatting
yaooqinn commented on pull request #28673: URL: https://github.com/apache/spark/pull/28673#issuecomment-635844180 cc @cloud-fan @MaxGekk @maropu thanks very much This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] maropu commented on pull request #18323: [SPARK-21117][SQL] Built-in SQL Function Support - WIDTH_BUCKET
maropu commented on pull request #18323: URL: https://github.com/apache/spark/pull/18323#issuecomment-635844301 Could you solve the conflict? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] yaooqinn commented on a change in pull request #28673: [SPARK-31867][SQL] Fix silent data change for datetime formatting
yaooqinn commented on a change in pull request #28673: URL: https://github.com/apache/spark/pull/28673#discussion_r432334147 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeFormatterHelper.scala ## @@ -118,6 +118,31 @@ trait DateTimeFormatterHelper { s"before Spark 3.0, or set to CORRECTED and treat it as an invalid datetime string.", e) } + // When legacy time parser policy set to EXCEPTION, check whether we will get different results + // between legacy formatter and new formatter. If new formatter fails but legacy formatter works, + // throw a SparkUpgradeException. On the contrary, if the legacy policy set to CORRECTED, + // DateTimeParseException will address by the caller side. + protected def checkDiffFormatResult[T <: Date]( + d: T, + legacyFormatFunc: T => String): PartialFunction[Throwable, String] = { +case e if needConvertToSparkUpgradeException(e) => + val resultCandidate = try { + legacyFormatFunc(d) +} catch { + case _: Throwable => throw e +} +throw new SparkUpgradeException("3.0", s"Fail to format '$resultCandidate' in the new" + + s" formatter. You can set ${SQLConf.LEGACY_TIME_PARSER_POLICY.key} to LEGACY to restore" + + s" the behavior before Spark 3.0, or set to CORRECTED and treat it as an invalid" + + s" datetime string.", e) + } + + private def needConvertToSparkUpgradeException(e: Throwable): Boolean = e match { +case _: DateTimeException | _: ArrayIndexOutOfBoundsException Review comment: Shall we use Nonfatal here? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] SparkQA commented on pull request #28593: [SPARK-31710][SQL] Fail casting numeric to timestamp by default
SparkQA commented on pull request #28593: URL: https://github.com/apache/spark/pull/28593#issuecomment-635846348 **[Test build #123277 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/123277/testReport)** for PR 28593 at commit [`7637256`](https://github.com/apache/spark/commit/7637256038c483b35b615bfc824bcb3867d4cc9f). This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins commented on pull request #28593: [SPARK-31710][SQL] Fail casting numeric to timestamp by default
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[GitHub] [spark] Deegue commented on a change in pull request #26422: [SPARK-29786][SQL] Fix MetaException when dropping a partition not exists on HDFS
Deegue commented on a change in pull request #26422: URL: https://github.com/apache/spark/pull/26422#discussion_r432336314 ## File path: sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveClientImpl.scala ## @@ -638,6 +644,17 @@ private[hive] class HiveClientImpl( s"No partition is dropped. One partition spec '$s' does not exist in table '$table' " + s"database '$db'") } +// Check whether the partition we are going to drop is empty. +// We make a dummy one for the empty partition. See [SPARK-29786] for more details. +parts.foreach { partition => + val partPath = partition.getPath.head + if (isExistPath(partPath)) { +val fs = partPath.getFileSystem(conf) +fs.mkdirs(partPath) +fs.deleteOnExit(partPath) + } Review comment: > I'm confused. When the partition exists (`isExistPath` returns true), why you need to mkdir it again? Sorry, I mistakenly delete `!` when adjusting the code .. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] [spark] SparkQA commented on pull request #28648: [SPARK-31788][CORE][DSTREAM][PYTHON] Recover the support of union for different types of RDD and DStreams
SparkQA commented on pull request #28648: URL: https://github.com/apache/spark/pull/28648#issuecomment-635848051 **[Test build #123275 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/123275/testReport)** for PR 28648 at commit [`a7b2af4`](https://github.com/apache/spark/commit/a7b2af405e6050372930c41181ccb974210f262f). * This patch **fails PySpark unit tests**. * This patch merges cleanly. * This patch adds the following public classes _(experimental)_: * `raise TypeError(\"Unsupported Java RDD class %s\" % cls_name)` This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] [spark] AmplabJenkins commented on pull request #28648: [SPARK-31788][CORE][DSTREAM][PYTHON] Recover the support of union for different types of RDD and DStreams
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