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[GitHub] [spark] AngersZhuuuu commented on a change in pull request #29966: [SPARK-33084][CORE][SQL] Add jar support ivy path

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AngersZh commented on a change in pull request #29966: URL: https://github.com/apache/spark/pull/29966#discussion_r529267930 ## File path: core/src/main/scala/org/apache/spark/util/Utils.scala ## @@ -2980,6 +2980,75 @@ private[spark] object Utils extends Logging { meta

[GitHub] [spark] beliefer opened a new pull request #30479: [SPARK-33527][SQL] Extend the function of decode so as consistent with mainstream databases

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beliefer opened a new pull request #30479: URL: https://github.com/apache/spark/pull/30479 ### What changes were proposed in this pull request? In Spark, decode(bin, charset) - Decodes the first argument using the second argument character set. Unfortunately this is NOT what any o

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[GitHub] [spark] imback82 commented on a change in pull request #30475: [SPARK-33522][SQL] Improve exception messages while handling UnresolvedTableOrView

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[GitHub] [spark] AngersZhuuuu commented on a change in pull request #29966: [SPARK-33084][CORE][SQL] Add jar support ivy path

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[GitHub] [spark] zhengruifeng commented on a change in pull request #30468: [SPARK-33518][ML][WIP] Improve performance of ML ALS recommendForAll by GEMV

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zhengruifeng commented on a change in pull request #30468: URL: https://github.com/apache/spark/pull/30468#discussion_r529256642 ## File path: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala ## @@ -551,6 +563,21 @@ object ALSModel extends MLReadable[ALSModel]

[GitHub] [spark] maropu commented on a change in pull request #30440: [SPARK-33496][SQL]Improve error message of ANSI explicit cast

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maropu commented on a change in pull request #30440: URL: https://github.com/apache/spark/pull/30440#discussion_r529251244 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala ## @@ -1783,6 +1798,14 @@ case class AnsiCast(child: Expres

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[GitHub] [spark] cloud-fan commented on a change in pull request #30412: [SPARK-33480][SQL] Support char/varchar type

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cloud-fan commented on a change in pull request #30412: URL: https://github.com/apache/spark/pull/30412#discussion_r529253616 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataType.scala ## @@ -124,13 +125,16 @@ abstract class DataType extends AbstractDat

[GitHub] [spark] cloud-fan commented on a change in pull request #30412: [SPARK-33480][SQL] Support char/varchar type

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AngersZh commented on a change in pull request #29966: URL: https://github.com/apache/spark/pull/29966#discussion_r529246237 ## File path: core/src/main/scala/org/apache/spark/SparkContext.scala ## @@ -1920,17 +1920,23 @@ class SparkContext(config: SparkConf) extends Loggin

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[GitHub] [spark] AngersZhuuuu commented on a change in pull request #29966: [SPARK-33084][CORE][SQL] Add jar support ivy path

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AngersZh commented on a change in pull request #29966: URL: https://github.com/apache/spark/pull/29966#discussion_r529245629 ## File path: docs/sql-ref-syntax-aux-resource-mgmt-add-jar.md ## @@ -33,7 +33,7 @@ ADD JAR file_name * **file_name** -The name of the JAR f

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[GitHub] [spark] ulysses-you commented on pull request #30315: [SPARK-33388][SQL] Merge In and InSet predicate

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ulysses-you commented on pull request #30315: URL: https://github.com/apache/spark/pull/30315#issuecomment-732698682 I think that the merge is not only code side. We have many code place use the `In` and `InSet`, if we decide to merge them then the origin idea should like that how to promi

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maropu commented on a change in pull request #29966: URL: https://github.com/apache/spark/pull/29966#discussion_r529239846 ## File path: core/src/main/scala/org/apache/spark/util/Utils.scala ## @@ -2980,6 +2980,75 @@ private[spark] object Utils extends Logging { metadata.t

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maropu commented on a change in pull request #29966: URL: https://github.com/apache/spark/pull/29966#discussion_r529226242 ## File path: core/src/main/scala/org/apache/spark/SparkContext.scala ## @@ -1920,17 +1920,23 @@ class SparkContext(config: SparkConf) extends Logging {

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[GitHub] [spark] HyukjinKwon commented on a change in pull request #30474: [SPARK-33521][SQL] Universal type conversion in resolving V2 partition specs

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HyukjinKwon commented on a change in pull request #30474: URL: https://github.com/apache/spark/pull/30474#discussion_r529235952 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolvePartitionSpec.scala ## @@ -65,31 +65,8 @@ object ResolveParti

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MaxGekk commented on a change in pull request #30474: URL: https://github.com/apache/spark/pull/30474#discussion_r529228577 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolvePartitionSpec.scala ## @@ -65,31 +65,8 @@ object ResolvePartition

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[GitHub] [spark] guiyanakuang commented on pull request #30467: [SPARK-32002][SQL]Support ExtractValue from nested ArrayStruct

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guiyanakuang commented on pull request #30467: URL: https://github.com/apache/spark/pull/30467#issuecomment-732677466 > Hmm, yeah, I remember the discussion with @cloud-fan. IIUC, it is not supported explicitly in Spark. Does this mean I need to close the pr? --

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[GitHub] [spark] ulysses-you commented on pull request #29490: [SPARK-32668][SQL] HiveGenericUDTF initialize UDTF should use StructObjectInspector method

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zhengruifeng commented on pull request #30468: URL: https://github.com/apache/spark/pull/30468#issuecomment-732673641 commit 543a41f: scala> val start = System.currentTimeMillis; start: Long = 1606185191500 scala> model.recommendForAllUsers(10).count res1: Long = 283228

[GitHub] [spark] guiyanakuang commented on pull request #30467: [SPARK-32002][SQL]Support ExtractValue from nested ArrayStruct

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guiyanakuang commented on pull request #30467: URL: https://github.com/apache/spark/pull/30467#issuecomment-732673623 > I remember the related discussion in #29645 Btw, other systems support this resolution? Google BigQuery and Amazon Athena are supposed to support nested arrays, but

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