[GitHub] spark issue #23169: [SPARK-26103][SQL] Limit the length of debug strings for...
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[GitHub] spark issue #22612: [SPARK-24958] Add executors' process tree total memory i...
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[GitHub] spark pull request #23203: [SPARK-26252][PYTHON] Add support to run specific...
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/23203#discussion_r238887812
--- Diff: python/run-tests.py ---
@@ -93,17 +93,18 @@ def run_individual_python_test(target_dir, test_name,
pyspark_python):
"pyspark-shell"
]
env["PYSPARK_SUBMIT_ARGS"] = " ".join(spark_args)
-
-LOGGER.info("Starting test(%s): %s", pyspark_python, test_name)
+str_test_name = " ".join(test_name)
+LOGGER.info("Starting test(%s): %s", pyspark_python, str_test_name)
start_time = time.time()
try:
per_test_output = tempfile.TemporaryFile()
retcode = subprocess.Popen(
-[os.path.join(SPARK_HOME, "bin/pyspark"), test_name],
--- End diff --
Oh, yea. Looks that's going to reduce the diff. Let me try.
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[GitHub] spark pull request #23220: [SPARK-25877][k8s] Move all feature logic to feat...
GitHub user vanzin opened a pull request: https://github.com/apache/spark/pull/23220 [SPARK-25877][k8s] Move all feature logic to feature classes. This change makes the driver and executor builders a lot simpler by encapsulating almost all feature logic into the respective feature classes. The only logic that remains is the creation of the initial pod, which needs to happen before anything else so is better to be left in the builder class. Most feature classes already behave fine when the config has nothing they should handle, but a few minor tweaks had to be added. Unit tests were also updated or added to account for these. The builder suites were simplified a lot and just test the remaining pod-related code in the builders themselves. You can merge this pull request into a Git repository by running: $ git pull https://github.com/vanzin/spark SPARK-25877 Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/23220.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #23220 commit a13bafd8e48d8a03fa35c6ff6817f03908f17e2d Author: Marcelo Vanzin Date: 2018-12-04T19:42:31Z [SPARK-25877][k8s] Move all feature logic to feature classes. This change makes the driver and executor builders a lot simpler by encapsulating almost all feature logic into the respective feature classes. The only logic that remains is the creation of the initial pod, which needs to happen before anything else so is better to be left in the builder class. Most feature classes already behave fine when the config has nothing they should handle, but a few minor tweaks had to be added. Unit tests were also updated or added to account for these. The builder suites were simplified a lot and just test the remaining pod-related code in the builders themselves. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #23220: [SPARK-25877][k8s] Move all feature logic to feature cla...
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[GitHub] spark pull request #22721: [SPARK-19784][SPARK-25403][SQL] Refresh the table...
Github user wangyum commented on a diff in the pull request:
https://github.com/apache/spark/pull/22721#discussion_r238891454
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/CommandUtils.scala
---
@@ -45,6 +45,8 @@ object CommandUtils extends Logging {
} else {
catalog.alterTableStats(table.identifier, None)
}
+} else {
+ catalog.refreshTable(table.identifier)
--- End diff --
Sure. move to DDLs is better.
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[GitHub] spark issue #23196: [SPARK-26243][SQL] Use java.time API for parsing timesta...
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[GitHub] spark issue #23108: [Spark-25993][SQL][TEST]Add test cases for CREATE EXTERN...
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[GitHub] spark pull request #23216: [SPARK-26264][CORE]It is better to add @transient...
Github user HyukjinKwon commented on a diff in the pull request: https://github.com/apache/spark/pull/23216#discussion_r238892679 --- Diff: core/src/main/scala/org/apache/spark/scheduler/ResultTask.scala --- @@ -56,7 +56,7 @@ private[spark] class ResultTask[T, U]( stageAttemptId: Int, taskBinary: Broadcast[Array[Byte]], partition: Partition, -locs: Seq[TaskLocation], +@transient private var locs: Seq[TaskLocation], --- End diff -- why is it `var` BTW? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #23108: [Spark-25993][SQL][TEST]Add test cases for CREATE EXTERN...
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[GitHub] spark issue #22721: [SPARK-19784][SPARK-25403][SQL] Refresh the table even t...
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[GitHub] spark pull request #23221: [SPARK-24243][CORE] Expose exceptions from InProc...
GitHub user vanzin opened a pull request: https://github.com/apache/spark/pull/23221 [SPARK-24243][CORE] Expose exceptions from InProcessAppHandle ## What changes were proposed in this pull request? Adds a new method to SparkAppHandle called getError which returns the exception (if present) that caused the underlying Spark app to fail. ## How was this patch tested? New tests added to SparkLauncherSuite for the new method. Closes #21849 You can merge this pull request into a Git repository by running: $ git pull https://github.com/vanzin/spark SPARK-24243 Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/23221.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #23221 commit 9240b77078936dceaaa4a68f6a54c5c0c16aab73 Author: Sahil Takiar Date: 2018-07-23T17:31:24Z [SPARK-24243][CORE] Expose exceptions from InProcessAppHandle Adds a new method to `SparkAppHandle` called `getError` which returns the exception (if present) that caused the underlying Spark app to fail. New tests added to `SparkLauncherSuite` for the new method. commit 29f1436e14b453b41b055be6b4e124c5eae7d8ff Author: Marcelo Vanzin Date: 2018-12-05T00:37:58Z Merge branch 'master' into SPARK-24243 commit e58fc919355c48d2d3b1cacb4d0ee18036cacbc6 Author: Marcelo Vanzin Date: 2018-12-05T00:41:44Z Feedback. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #23221: [SPARK-24243][CORE] Expose exceptions from InProcessAppH...
Github user vanzin commented on the issue: https://github.com/apache/spark/pull/23221 I applied my own feedback to the original PR and will merge pending tests (since it was already reviewed), unless someone comments first. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #22468: [SPARK-25374][SQL] SafeProjection supports fallba...
Github user maropu commented on a diff in the pull request:
https://github.com/apache/spark/pull/22468#discussion_r238894837
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala
---
@@ -535,4 +535,98 @@ class UnsafeRowConverterSuite extends SparkFunSuite
with Matchers with PlanTestB
assert(unsafeRow.getSizeInBytes ==
8 + 8 * 2 + roundedSize(field1.getSizeInBytes) +
roundedSize(field2.getSizeInBytes))
}
+
+ testBothCodegenAndInterpreted("SPARK-25374 converts back into safe
representation") {
+def convertBackToInternalRow(inputRow: InternalRow, fields:
Array[DataType]): InternalRow = {
+ val unsafeProj = UnsafeProjection.create(fields)
+ val unsafeRow = unsafeProj(inputRow)
+ val safeProj = SafeProjection.create(fields)
+ safeProj(unsafeRow)
+}
+
+// Simple tests
+val inputRow = InternalRow.fromSeq(Seq(
+ false, 3.toByte, 15.toShort, -83, 129L, 1.0f, 8.0,
UTF8String.fromString("test"),
+ Decimal(255), CalendarInterval.fromString("interval 1 day"),
Array[Byte](1, 2)
+))
+val fields1 = Array(
+ BooleanType, ByteType, ShortType, IntegerType, LongType, FloatType,
+ DoubleType, StringType, DecimalType.defaultConcreteType,
CalendarIntervalType,
+ BinaryType)
+
+assert(convertBackToInternalRow(inputRow, fields1) === inputRow)
+
+// Array tests
+val arrayRow = InternalRow.fromSeq(Seq(
+ createArray(1, 2, 3),
+ createArray(
+createArray(Seq("a", "b", "c").map(UTF8String.fromString): _*),
+createArray(Seq("d").map(UTF8String.fromString): _*))
+))
+val fields2 = Array[DataType](
+ ArrayType(IntegerType),
+ ArrayType(ArrayType(StringType)))
+
+assert(convertBackToInternalRow(arrayRow, fields2) === arrayRow)
+
+// Struct tests
+val structRow = InternalRow.fromSeq(Seq(
+ InternalRow.fromSeq(Seq[Any](1, 4.0)),
+ InternalRow.fromSeq(Seq(
+UTF8String.fromString("test"),
+InternalRow.fromSeq(Seq(
+ 1,
+ createArray(Seq("2", "3").map(UTF8String.fromString): _*)
+))
+ ))
+))
+val fields3 = Array[DataType](
+ StructType(
+StructField("c0", IntegerType) ::
+StructField("c1", DoubleType) ::
+Nil),
+ StructType(
+StructField("c2", StringType) ::
+StructField("c3", StructType(
+ StructField("c4", IntegerType) ::
+ StructField("c5", ArrayType(StringType)) ::
+ Nil)) ::
+Nil))
+
+assert(convertBackToInternalRow(structRow, fields3) === structRow)
+
+// Map tests
+val mapRow = InternalRow.fromSeq(Seq(
+ createMap(Seq("k1", "k2").map(UTF8String.fromString): _*)(1, 2),
+ createMap(
+createMap(3, 5)(Seq("v1", "v2").map(UTF8String.fromString): _*),
+createMap(7, 9)(Seq("v3", "v4").map(UTF8String.fromString): _*)
+ )(
+createMap(Seq("k3", "k4").map(UTF8String.fromString):
_*)(3.toShort, 4.toShort),
+createMap(Seq("k5", "k6").map(UTF8String.fromString):
_*)(5.toShort, 6.toShort)
+ )))
+val fields4 = Array[DataType](
+ MapType(StringType, IntegerType),
+ MapType(MapType(IntegerType, StringType), MapType(StringType,
ShortType)))
+
+val mapResultRow = convertBackToInternalRow(mapRow,
fields4).toSeq(fields4)
+val mapExpectedRow = mapRow.toSeq(fields4)
+// Since `ArrayBasedMapData` does not override `equals` and `hashCode`,
--- End diff --
Aha, thanks. I remember that its related to SPARK-18134.
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[GitHub] spark pull request #23213: [SPARK-26262][SQL] Run SQLQueryTestSuite with WHO...
Github user maropu commented on a diff in the pull request:
https://github.com/apache/spark/pull/23213#discussion_r238895286
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/SQLQueryTestSuite.scala ---
@@ -144,9 +144,10 @@ class SQLQueryTestSuite extends QueryTest with
SharedSQLContext {
val (comments, code) = input.split("\n").partition(_.startsWith("--"))
// Runs all the tests on both codegen-only and interpreter modes
-val codegenConfigSets = Array(CODEGEN_ONLY, NO_CODEGEN).map {
- case codegenFactoryMode =>
-Array(SQLConf.CODEGEN_FACTORY_MODE.key ->
codegenFactoryMode.toString)
+val codegenConfigSets = Array(("false", "NO_CODEGEN"), ("true",
"CODEGEN_ONLY")).map {
--- End diff --
I will check the time later, too.
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[GitHub] spark issue #23218: [SPARK-26266][BUILD] Update to Scala 2.12.8
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[GitHub] spark issue #23216: [SPARK-26264][CORE]It is better to add @transient to fie...
Github user 10110346 commented on the issue:
https://github.com/apache/spark/pull/23216
>
>
> Are you sure it's even a field in the class? it looks like it's only used
to define this:
>
> ```
> @transient private[this] val preferredLocs: Seq[TaskLocation] = {
> if (locs == null) Nil else locs.toSet.toSeq
> }
> ```
>
> I'd expect Scala would not generate a field. Indeed the thing it is used
to make is transient.
Yeah, it would not generate a field, thanks @srowen
By the way, is it better to remove `transient` for `ShuffleMapTask`?
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[GitHub] spark pull request #23213: [SPARK-26262][SQL] Runs SQLQueryTestSuite on mixe...
Github user maropu commented on a diff in the pull request:
https://github.com/apache/spark/pull/23213#discussion_r238899777
--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
---
@@ -2899,6 +2899,144 @@ class SQLQuerySuite extends QueryTest with
SharedSQLContext {
}
}
}
+
+ private def checkKeywordsExistsInExplain(df: DataFrame, keywords:
String*): Unit = {
+val output = new java.io.ByteArrayOutputStream()
+Console.withOut(output) {
+ df.explain(extended = true)
+}
+val normalizedOutput = output.toString.replaceAll("#\\d+", "#x")
+for (key <- keywords) {
+ assert(normalizedOutput.contains(key))
+}
+ }
+
+ test("optimized plan should show the rewritten aggregate expression") {
--- End diff --
updated! Thanks, guys!
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[GitHub] spark pull request #22514: [SPARK-25271][SQL] Hive ctas commands should use ...
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22514#discussion_r238899698
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala ---
@@ -181,62 +180,39 @@ case class RelationConversions(
conf: SQLConf,
sessionCatalog: HiveSessionCatalog) extends Rule[LogicalPlan] {
private def isConvertible(relation: HiveTableRelation): Boolean = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-serde.contains("parquet") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
- serde.contains("orc") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_ORC)
+isConvertible(relation.tableMeta)
}
- // Return true for Apache ORC and Hive ORC-related configuration names.
- // Note that Spark doesn't support configurations like
`hive.merge.orcfile.stripe.level`.
- private def isOrcProperty(key: String) =
-key.startsWith("orc.") || key.contains(".orc.")
-
- private def isParquetProperty(key: String) =
-key.startsWith("parquet.") || key.contains(".parquet.")
-
- private def convert(relation: HiveTableRelation): LogicalRelation = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-
-// Consider table and storage properties. For properties existing in
both sides, storage
-// properties will supersede table properties.
-if (serde.contains("parquet")) {
- val options =
relation.tableMeta.properties.filterKeys(isParquetProperty) ++
-relation.tableMeta.storage.properties +
(ParquetOptions.MERGE_SCHEMA ->
-
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET_WITH_SCHEMA_MERGING).toString)
- sessionCatalog.metastoreCatalog
-.convertToLogicalRelation(relation, options,
classOf[ParquetFileFormat], "parquet")
-} else {
- val options =
relation.tableMeta.properties.filterKeys(isOrcProperty) ++
-relation.tableMeta.storage.properties
- if (conf.getConf(SQLConf.ORC_IMPLEMENTATION) == "native") {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
-
classOf[org.apache.spark.sql.execution.datasources.orc.OrcFileFormat],
- "orc")
- } else {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
- classOf[org.apache.spark.sql.hive.orc.OrcFileFormat],
- "orc")
- }
-}
+ private def isConvertible(tableMeta: CatalogTable): Boolean = {
+val serde =
tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
+serde.contains("parquet") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
+ serde.contains("orc") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_ORC)
}
+ private val metastoreCatalog = sessionCatalog.metastoreCatalog
+
override def apply(plan: LogicalPlan): LogicalPlan = {
plan resolveOperators {
// Write path
case InsertIntoTable(r: HiveTableRelation, partition, query,
overwrite, ifPartitionNotExists)
// Inserting into partitioned table is not supported in
Parquet/Orc data source (yet).
if query.resolved && DDLUtils.isHiveTable(r.tableMeta) &&
!r.isPartitioned && isConvertible(r) =>
-InsertIntoTable(convert(r), partition, query, overwrite,
ifPartitionNotExists)
+InsertIntoTable(metastoreCatalog.convert(r), partition,
+ query, overwrite, ifPartitionNotExists)
// Read path
case relation: HiveTableRelation
if DDLUtils.isHiveTable(relation.tableMeta) &&
isConvertible(relation) =>
-convert(relation)
+metastoreCatalog.convert(relation)
+
+ // CTAS
+ case CreateTable(tableDesc, mode, Some(query))
+ if DDLUtils.isHiveTable(tableDesc) &&
tableDesc.partitionColumnNames.isEmpty &&
+isConvertible(tableDesc) =>
--- End diff --
It's not a new optimization... It's an optimization we dropped in 2.3 by
mistake.
I'm fine to add a config with default value true.
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[GitHub] spark issue #23217: [SPARK-25829][SQL][FOLLOWUP] Refactor MapConcat in order...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/23217 thanks, merging to master! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #23217: [SPARK-25829][SQL][FOLLOWUP] Refactor MapConcat i...
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[GitHub] spark pull request #22514: [SPARK-25271][SQL] Hive ctas commands should use ...
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/22514#discussion_r238902415
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala ---
@@ -181,62 +180,39 @@ case class RelationConversions(
conf: SQLConf,
sessionCatalog: HiveSessionCatalog) extends Rule[LogicalPlan] {
private def isConvertible(relation: HiveTableRelation): Boolean = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-serde.contains("parquet") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
- serde.contains("orc") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_ORC)
+isConvertible(relation.tableMeta)
}
- // Return true for Apache ORC and Hive ORC-related configuration names.
- // Note that Spark doesn't support configurations like
`hive.merge.orcfile.stripe.level`.
- private def isOrcProperty(key: String) =
-key.startsWith("orc.") || key.contains(".orc.")
-
- private def isParquetProperty(key: String) =
-key.startsWith("parquet.") || key.contains(".parquet.")
-
- private def convert(relation: HiveTableRelation): LogicalRelation = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-
-// Consider table and storage properties. For properties existing in
both sides, storage
-// properties will supersede table properties.
-if (serde.contains("parquet")) {
- val options =
relation.tableMeta.properties.filterKeys(isParquetProperty) ++
-relation.tableMeta.storage.properties +
(ParquetOptions.MERGE_SCHEMA ->
-
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET_WITH_SCHEMA_MERGING).toString)
- sessionCatalog.metastoreCatalog
-.convertToLogicalRelation(relation, options,
classOf[ParquetFileFormat], "parquet")
-} else {
- val options =
relation.tableMeta.properties.filterKeys(isOrcProperty) ++
-relation.tableMeta.storage.properties
- if (conf.getConf(SQLConf.ORC_IMPLEMENTATION) == "native") {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
-
classOf[org.apache.spark.sql.execution.datasources.orc.OrcFileFormat],
- "orc")
- } else {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
- classOf[org.apache.spark.sql.hive.orc.OrcFileFormat],
- "orc")
- }
-}
+ private def isConvertible(tableMeta: CatalogTable): Boolean = {
+val serde =
tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
+serde.contains("parquet") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
+ serde.contains("orc") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_ORC)
}
+ private val metastoreCatalog = sessionCatalog.metastoreCatalog
+
override def apply(plan: LogicalPlan): LogicalPlan = {
plan resolveOperators {
// Write path
case InsertIntoTable(r: HiveTableRelation, partition, query,
overwrite, ifPartitionNotExists)
// Inserting into partitioned table is not supported in
Parquet/Orc data source (yet).
if query.resolved && DDLUtils.isHiveTable(r.tableMeta) &&
!r.isPartitioned && isConvertible(r) =>
-InsertIntoTable(convert(r), partition, query, overwrite,
ifPartitionNotExists)
+InsertIntoTable(metastoreCatalog.convert(r), partition,
+ query, overwrite, ifPartitionNotExists)
// Read path
case relation: HiveTableRelation
if DDLUtils.isHiveTable(relation.tableMeta) &&
isConvertible(relation) =>
-convert(relation)
+metastoreCatalog.convert(relation)
+
+ // CTAS
+ case CreateTable(tableDesc, mode, Some(query))
+ if DDLUtils.isHiveTable(tableDesc) &&
tableDesc.partitionColumnNames.isEmpty &&
+isConvertible(tableDesc) =>
--- End diff --
hmm, the optimization is already controlled by configs like
`HiveUtils.CONVERT_METASTORE_ORC` and `HiveUtils.CONVERT_METASTORE_PARQUET`. Do
we need another config for it?
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[GitHub] spark issue #23216: [SPARK-26264][CORE]It is better to add @transient to fie...
Github user srowen commented on the issue: https://github.com/apache/spark/pull/23216 I think just leave it. The `@transient` in `ShuffleMapTasks`'s `locs` is just superfluous here, not sure it's worth changing. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #23216: [SPARK-26264][CORE]It is better to add @transient...
Github user 10110346 closed the pull request at: https://github.com/apache/spark/pull/23216 --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #23216: [SPARK-26264][CORE]It is better to add @transient to fie...
Github user 10110346 commented on the issue: https://github.com/apache/spark/pull/23216 Ok, I will close this PR, thank you very much --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #23213: [SPARK-26262][SQL] Runs SQLQueryTestSuite on mixe...
Github user maropu commented on a diff in the pull request:
https://github.com/apache/spark/pull/23213#discussion_r238905795
--- Diff: sql/core/src/test/scala/org/apache/spark/sql/ExplainSuite.scala
---
@@ -53,6 +55,133 @@ class ExplainSuite extends QueryTest with
SharedSQLContext {
checkKeywordsExistsInExplain(df,
keywords = "InMemoryRelation", "StorageLevel(disk, memory,
deserialized, 1 replicas)")
}
+
+ test("optimized plan should show the rewritten aggregate expression") {
+withTempView("test_agg") {
+ sql(
+"""
+ |CREATE TEMPORARY VIEW test_agg AS SELECT * FROM VALUES
+ | (1, true), (1, false),
+ | (2, true),
+ | (3, false), (3, null),
+ | (4, null), (4, null),
+ | (5, null), (5, true), (5, false) AS test_agg(k, v)
+""".stripMargin)
+
+ // simple explain of queries having every/some/any aggregates.
Optimized
+ // plan should show the rewritten aggregate expression.
+ val df = sql("SELECT k, every(v), some(v), any(v) FROM test_agg
GROUP BY k")
+ checkKeywordsExistsInExplain(df,
+"Aggregate [k#x], [k#x, min(v#x) AS every(v)#x, max(v#x) AS
some(v)#x, " +
--- End diff --
I forgot to set true at extended in explain...
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[GitHub] spark issue #21486: [SPARK-24387][Core] Heartbeat-timeout executor is added ...
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[GitHub] spark issue #23213: [SPARK-26262][SQL] Runs SQLQueryTestSuite on mixed confi...
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[GitHub] spark issue #23213: [SPARK-26262][SQL] Runs SQLQueryTestSuite on mixed confi...
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[GitHub] spark issue #23213: [SPARK-26262][SQL] Runs SQLQueryTestSuite on mixed confi...
Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/23213 **[Test build #99692 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/99692/testReport)** for PR 23213 at commit [`808af50`](https://github.com/apache/spark/commit/808af50d756583bd69b7dd7ca1e1ae09d2457b41). --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #23218: [SPARK-26266][BUILD] Update to Scala 2.12.8
Github user srowen commented on the issue: https://github.com/apache/spark/pull/23218 Hm, one failure was due to a JVM crash, but it fails twice consistent, with sbt just exiting with status 134. No other failures are logged. Not sure what to make of that! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #23210: [SPARK-26233][SQL] CheckOverflow when encoding a decimal...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/23210 a late LGTM --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #22514: [SPARK-25271][SQL] Hive ctas commands should use ...
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22514#discussion_r238908877
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala ---
@@ -181,62 +180,39 @@ case class RelationConversions(
conf: SQLConf,
sessionCatalog: HiveSessionCatalog) extends Rule[LogicalPlan] {
private def isConvertible(relation: HiveTableRelation): Boolean = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-serde.contains("parquet") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
- serde.contains("orc") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_ORC)
+isConvertible(relation.tableMeta)
}
- // Return true for Apache ORC and Hive ORC-related configuration names.
- // Note that Spark doesn't support configurations like
`hive.merge.orcfile.stripe.level`.
- private def isOrcProperty(key: String) =
-key.startsWith("orc.") || key.contains(".orc.")
-
- private def isParquetProperty(key: String) =
-key.startsWith("parquet.") || key.contains(".parquet.")
-
- private def convert(relation: HiveTableRelation): LogicalRelation = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-
-// Consider table and storage properties. For properties existing in
both sides, storage
-// properties will supersede table properties.
-if (serde.contains("parquet")) {
- val options =
relation.tableMeta.properties.filterKeys(isParquetProperty) ++
-relation.tableMeta.storage.properties +
(ParquetOptions.MERGE_SCHEMA ->
-
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET_WITH_SCHEMA_MERGING).toString)
- sessionCatalog.metastoreCatalog
-.convertToLogicalRelation(relation, options,
classOf[ParquetFileFormat], "parquet")
-} else {
- val options =
relation.tableMeta.properties.filterKeys(isOrcProperty) ++
-relation.tableMeta.storage.properties
- if (conf.getConf(SQLConf.ORC_IMPLEMENTATION) == "native") {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
-
classOf[org.apache.spark.sql.execution.datasources.orc.OrcFileFormat],
- "orc")
- } else {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
- classOf[org.apache.spark.sql.hive.orc.OrcFileFormat],
- "orc")
- }
-}
+ private def isConvertible(tableMeta: CatalogTable): Boolean = {
+val serde =
tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
+serde.contains("parquet") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
+ serde.contains("orc") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_ORC)
}
+ private val metastoreCatalog = sessionCatalog.metastoreCatalog
+
override def apply(plan: LogicalPlan): LogicalPlan = {
plan resolveOperators {
// Write path
case InsertIntoTable(r: HiveTableRelation, partition, query,
overwrite, ifPartitionNotExists)
// Inserting into partitioned table is not supported in
Parquet/Orc data source (yet).
if query.resolved && DDLUtils.isHiveTable(r.tableMeta) &&
!r.isPartitioned && isConvertible(r) =>
-InsertIntoTable(convert(r), partition, query, overwrite,
ifPartitionNotExists)
+InsertIntoTable(metastoreCatalog.convert(r), partition,
+ query, overwrite, ifPartitionNotExists)
// Read path
case relation: HiveTableRelation
if DDLUtils.isHiveTable(relation.tableMeta) &&
isConvertible(relation) =>
-convert(relation)
+metastoreCatalog.convert(relation)
+
+ // CTAS
+ case CreateTable(tableDesc, mode, Some(query))
+ if DDLUtils.isHiveTable(tableDesc) &&
tableDesc.partitionColumnNames.isEmpty &&
+isConvertible(tableDesc) =>
--- End diff --
I don't mind to add `HiveUtils.CONVERT_METASTORE_ORC_CTAS`, maybe we can do
it in a followup?
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[GitHub] spark pull request #22514: [SPARK-25271][SQL] Hive ctas commands should use ...
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/22514#discussion_r238909363
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala ---
@@ -181,62 +180,39 @@ case class RelationConversions(
conf: SQLConf,
sessionCatalog: HiveSessionCatalog) extends Rule[LogicalPlan] {
private def isConvertible(relation: HiveTableRelation): Boolean = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-serde.contains("parquet") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
- serde.contains("orc") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_ORC)
+isConvertible(relation.tableMeta)
}
- // Return true for Apache ORC and Hive ORC-related configuration names.
- // Note that Spark doesn't support configurations like
`hive.merge.orcfile.stripe.level`.
- private def isOrcProperty(key: String) =
-key.startsWith("orc.") || key.contains(".orc.")
-
- private def isParquetProperty(key: String) =
-key.startsWith("parquet.") || key.contains(".parquet.")
-
- private def convert(relation: HiveTableRelation): LogicalRelation = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-
-// Consider table and storage properties. For properties existing in
both sides, storage
-// properties will supersede table properties.
-if (serde.contains("parquet")) {
- val options =
relation.tableMeta.properties.filterKeys(isParquetProperty) ++
-relation.tableMeta.storage.properties +
(ParquetOptions.MERGE_SCHEMA ->
-
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET_WITH_SCHEMA_MERGING).toString)
- sessionCatalog.metastoreCatalog
-.convertToLogicalRelation(relation, options,
classOf[ParquetFileFormat], "parquet")
-} else {
- val options =
relation.tableMeta.properties.filterKeys(isOrcProperty) ++
-relation.tableMeta.storage.properties
- if (conf.getConf(SQLConf.ORC_IMPLEMENTATION) == "native") {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
-
classOf[org.apache.spark.sql.execution.datasources.orc.OrcFileFormat],
- "orc")
- } else {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
- classOf[org.apache.spark.sql.hive.orc.OrcFileFormat],
- "orc")
- }
-}
+ private def isConvertible(tableMeta: CatalogTable): Boolean = {
+val serde =
tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
+serde.contains("parquet") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
+ serde.contains("orc") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_ORC)
}
+ private val metastoreCatalog = sessionCatalog.metastoreCatalog
+
override def apply(plan: LogicalPlan): LogicalPlan = {
plan resolveOperators {
// Write path
case InsertIntoTable(r: HiveTableRelation, partition, query,
overwrite, ifPartitionNotExists)
// Inserting into partitioned table is not supported in
Parquet/Orc data source (yet).
if query.resolved && DDLUtils.isHiveTable(r.tableMeta) &&
!r.isPartitioned && isConvertible(r) =>
-InsertIntoTable(convert(r), partition, query, overwrite,
ifPartitionNotExists)
+InsertIntoTable(metastoreCatalog.convert(r), partition,
+ query, overwrite, ifPartitionNotExists)
// Read path
case relation: HiveTableRelation
if DDLUtils.isHiveTable(relation.tableMeta) &&
isConvertible(relation) =>
-convert(relation)
+metastoreCatalog.convert(relation)
+
+ // CTAS
+ case CreateTable(tableDesc, mode, Some(query))
+ if DDLUtils.isHiveTable(tableDesc) &&
tableDesc.partitionColumnNames.isEmpty &&
+isConvertible(tableDesc) =>
--- End diff --
ok.
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[GitHub] spark pull request #23207: [SPARK-26193][SQL] Implement shuffle write metric...
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/23207#discussion_r238909822
--- Diff: core/src/main/scala/org/apache/spark/shuffle/metrics.scala ---
@@ -50,3 +50,57 @@ private[spark] trait ShuffleWriteMetricsReporter {
private[spark] def decBytesWritten(v: Long): Unit
private[spark] def decRecordsWritten(v: Long): Unit
}
+
+
+/**
+ * A proxy class of ShuffleWriteMetricsReporter which proxy all metrics
updating to the input
+ * reporters.
+ */
+private[spark] class GroupedShuffleWriteMetricsReporter(
--- End diff --
For the write metrics, it's different. It's the default one calls the SQL
one, which needs to hack the default one to register external reporters.
Maybe we should not change the read side, just create a special
`PairShuffleWriteMetricsReporter` to update both the SQL reporter and default
reporter.
Another idea is, `ShuffleDependency` carries a `reporter => reporter`
function, instead of a reporter. Then we can create a SQL reporter which takes
another reporter(similar to read side), and put the SQL reporter's constructor
in `ShuffleDependency`.
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GitHub user gatorsmile opened a pull request: https://github.com/apache/spark/pull/23222 [SPARK-20636] Add the rule TransposeWindow to the optimization batch ## What changes were proposed in this pull request? This PR is a follow-up of the PR https://github.com/apache/spark/pull/17899. It is to add the rule the optimizer batch. ## How was this patch tested? The existing tests. You can merge this pull request into a Git repository by running: $ git pull https://github.com/gatorsmile/spark followupSPARK-20636 Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/23222.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #23222 commit 1270e89026d80c862137c03edbeee53e56f3ed6d Author: gatorsmile Date: 2018-12-05T05:07:00Z add the rule TransposeWindow to the batch --- - 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 pull request #22514: [SPARK-25271][SQL] Hive ctas commands should use ...
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/22514#discussion_r238933039
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala ---
@@ -181,62 +180,39 @@ case class RelationConversions(
conf: SQLConf,
sessionCatalog: HiveSessionCatalog) extends Rule[LogicalPlan] {
private def isConvertible(relation: HiveTableRelation): Boolean = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-serde.contains("parquet") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
- serde.contains("orc") &&
conf.getConf(HiveUtils.CONVERT_METASTORE_ORC)
+isConvertible(relation.tableMeta)
}
- // Return true for Apache ORC and Hive ORC-related configuration names.
- // Note that Spark doesn't support configurations like
`hive.merge.orcfile.stripe.level`.
- private def isOrcProperty(key: String) =
-key.startsWith("orc.") || key.contains(".orc.")
-
- private def isParquetProperty(key: String) =
-key.startsWith("parquet.") || key.contains(".parquet.")
-
- private def convert(relation: HiveTableRelation): LogicalRelation = {
-val serde =
relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
-
-// Consider table and storage properties. For properties existing in
both sides, storage
-// properties will supersede table properties.
-if (serde.contains("parquet")) {
- val options =
relation.tableMeta.properties.filterKeys(isParquetProperty) ++
-relation.tableMeta.storage.properties +
(ParquetOptions.MERGE_SCHEMA ->
-
conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET_WITH_SCHEMA_MERGING).toString)
- sessionCatalog.metastoreCatalog
-.convertToLogicalRelation(relation, options,
classOf[ParquetFileFormat], "parquet")
-} else {
- val options =
relation.tableMeta.properties.filterKeys(isOrcProperty) ++
-relation.tableMeta.storage.properties
- if (conf.getConf(SQLConf.ORC_IMPLEMENTATION) == "native") {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
-
classOf[org.apache.spark.sql.execution.datasources.orc.OrcFileFormat],
- "orc")
- } else {
-sessionCatalog.metastoreCatalog.convertToLogicalRelation(
- relation,
- options,
- classOf[org.apache.spark.sql.hive.orc.OrcFileFormat],
- "orc")
- }
-}
+ private def isConvertible(tableMeta: CatalogTable): Boolean = {
+val serde =
tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
+serde.contains("parquet") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_PARQUET) ||
+ serde.contains("orc") &&
SQLConf.get.getConf(HiveUtils.CONVERT_METASTORE_ORC)
}
+ private val metastoreCatalog = sessionCatalog.metastoreCatalog
+
override def apply(plan: LogicalPlan): LogicalPlan = {
plan resolveOperators {
// Write path
case InsertIntoTable(r: HiveTableRelation, partition, query,
overwrite, ifPartitionNotExists)
// Inserting into partitioned table is not supported in
Parquet/Orc data source (yet).
if query.resolved && DDLUtils.isHiveTable(r.tableMeta) &&
!r.isPartitioned && isConvertible(r) =>
-InsertIntoTable(convert(r), partition, query, overwrite,
ifPartitionNotExists)
+InsertIntoTable(metastoreCatalog.convert(r), partition,
+ query, overwrite, ifPartitionNotExists)
// Read path
case relation: HiveTableRelation
if DDLUtils.isHiveTable(relation.tableMeta) &&
isConvertible(relation) =>
-convert(relation)
+metastoreCatalog.convert(relation)
+
+ // CTAS
+ case CreateTable(tableDesc, mode, Some(query))
+ if DDLUtils.isHiveTable(tableDesc) &&
tableDesc.partitionColumnNames.isEmpty &&
+isConvertible(tableDesc) =>
--- End diff --
Since the regression was already introduced, we need to add a conf and
migration guide.
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[GitHub] spark issue #22683: [SPARK-25696] The storage memory displayed on spark Appl...
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[GitHub] spark issue #22683: [SPARK-25696] The storage memory displayed on spark Appl...
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