spark-instrumented-optimizer/dev/deps/spark-deps-hadoop-2.7-hive-2.3

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[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
HikariCP/2.5.1//HikariCP-2.5.1.jar
JLargeArrays/1.5//JLargeArrays-1.5.jar
JTransforms/3.1//JTransforms-3.1.jar
RoaringBitmap/0.9.0//RoaringBitmap-0.9.0.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
ST4/4.0.4//ST4-4.0.4.jar
activation/1.1.1//activation-1.1.1.jar
aircompressor/0.16//aircompressor-0.16.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
algebra_2.12/2.0.0-M2//algebra_2.12-2.0.0-M2.jar
annotations/17.0.0//annotations-17.0.0.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
antlr-runtime/3.5.2//antlr-runtime-3.5.2.jar
antlr4-runtime/4.8-1//antlr4-runtime-4.8-1.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
aopalliance-repackaged/2.6.1//aopalliance-repackaged-2.6.1.jar
aopalliance/1.0//aopalliance-1.0.jar
apacheds-i18n/2.0.0-M15//apacheds-i18n-2.0.0-M15.jar
apacheds-kerberos-codec/2.0.0-M15//apacheds-kerberos-codec-2.0.0-M15.jar
api-asn1-api/1.0.0-M20//api-asn1-api-1.0.0-M20.jar
api-util/1.0.0-M20//api-util-1.0.0-M20.jar
arpack_combined_all/0.1//arpack_combined_all-0.1.jar
arrow-format/2.0.0//arrow-format-2.0.0.jar
arrow-memory-core/2.0.0//arrow-memory-core-2.0.0.jar
arrow-memory-netty/2.0.0//arrow-memory-netty-2.0.0.jar
arrow-vector/2.0.0//arrow-vector-2.0.0.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
audience-annotations/0.5.0//audience-annotations-0.5.0.jar
automaton/1.11-8//automaton-1.11-8.jar
avro-ipc/1.10.1//avro-ipc-1.10.1.jar
avro-mapred/1.10.1//avro-mapred-1.10.1.jar
avro/1.10.1//avro-1.10.1.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
bonecp/0.8.0.RELEASE//bonecp-0.8.0.RELEASE.jar
breeze-macros_2.12/1.0//breeze-macros_2.12-1.0.jar
breeze_2.12/1.0//breeze_2.12-1.0.jar
cats-kernel_2.12/2.0.0-M4//cats-kernel_2.12-2.0.0-M4.jar
chill-java/0.9.5//chill-java-0.9.5.jar
chill_2.12/0.9.5//chill_2.12-0.9.5.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
commons-beanutils/1.9.4//commons-beanutils-1.9.4.jar
commons-cli/1.2//commons-cli-1.2.jar
commons-codec/1.15//commons-codec-1.15.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
commons-collections/3.2.2//commons-collections-3.2.2.jar
commons-compiler/3.0.16//commons-compiler-3.0.16.jar
commons-compress/1.20//commons-compress-1.20.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
commons-configuration/1.6//commons-configuration-1.6.jar
commons-crypto/1.1.0//commons-crypto-1.1.0.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
commons-dbcp/1.4//commons-dbcp-1.4.jar
commons-digester/1.8//commons-digester-1.8.jar
commons-httpclient/3.1//commons-httpclient-3.1.jar
commons-io/2.4//commons-io-2.4.jar
commons-lang/2.6//commons-lang-2.6.jar
commons-lang3/3.11//commons-lang3-3.11.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
commons-logging/1.1.3//commons-logging-1.1.3.jar
commons-math3/3.4.1//commons-math3-3.4.1.jar
commons-net/3.1//commons-net-3.1.jar
commons-pool/1.5.4//commons-pool-1.5.4.jar
commons-text/1.6//commons-text-1.6.jar
compress-lzf/1.0.3//compress-lzf-1.0.3.jar
core/1.1.2//core-1.1.2.jar
curator-client/2.7.1//curator-client-2.7.1.jar
curator-framework/2.7.1//curator-framework-2.7.1.jar
curator-recipes/2.7.1//curator-recipes-2.7.1.jar
datanucleus-api-jdo/4.2.4//datanucleus-api-jdo-4.2.4.jar
datanucleus-core/4.1.17//datanucleus-core-4.1.17.jar
datanucleus-rdbms/4.1.19//datanucleus-rdbms-4.1.19.jar
derby/10.14.2.0//derby-10.14.2.0.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
dropwizard-metrics-hadoop-metrics2-reporter/0.1.2//dropwizard-metrics-hadoop-metrics2-reporter-0.1.2.jar
flatbuffers-java/1.9.0//flatbuffers-java-1.9.0.jar
generex/1.0.2//generex-1.0.2.jar
gson/2.2.4//gson-2.2.4.jar
guava/14.0.1//guava-14.0.1.jar
guice-servlet/3.0//guice-servlet-3.0.jar
guice/3.0//guice-3.0.jar
hadoop-annotations/2.7.4//hadoop-annotations-2.7.4.jar
hadoop-auth/2.7.4//hadoop-auth-2.7.4.jar
hadoop-client/2.7.4//hadoop-client-2.7.4.jar
hadoop-common/2.7.4//hadoop-common-2.7.4.jar
hadoop-hdfs/2.7.4//hadoop-hdfs-2.7.4.jar
hadoop-mapreduce-client-app/2.7.4//hadoop-mapreduce-client-app-2.7.4.jar
hadoop-mapreduce-client-common/2.7.4//hadoop-mapreduce-client-common-2.7.4.jar
hadoop-mapreduce-client-core/2.7.4//hadoop-mapreduce-client-core-2.7.4.jar
hadoop-mapreduce-client-jobclient/2.7.4//hadoop-mapreduce-client-jobclient-2.7.4.jar
hadoop-mapreduce-client-shuffle/2.7.4//hadoop-mapreduce-client-shuffle-2.7.4.jar
hadoop-yarn-api/2.7.4//hadoop-yarn-api-2.7.4.jar
hadoop-yarn-client/2.7.4//hadoop-yarn-client-2.7.4.jar
hadoop-yarn-common/2.7.4//hadoop-yarn-common-2.7.4.jar
hadoop-yarn-server-common/2.7.4//hadoop-yarn-server-common-2.7.4.jar
hadoop-yarn-server-web-proxy/2.7.4//hadoop-yarn-server-web-proxy-2.7.4.jar
hive-beeline/2.3.8//hive-beeline-2.3.8.jar
hive-cli/2.3.8//hive-cli-2.3.8.jar
hive-common/2.3.8//hive-common-2.3.8.jar
hive-exec/2.3.8/core/hive-exec-2.3.8-core.jar
hive-jdbc/2.3.8//hive-jdbc-2.3.8.jar
hive-llap-common/2.3.8//hive-llap-common-2.3.8.jar
hive-metastore/2.3.8//hive-metastore-2.3.8.jar
hive-serde/2.3.8//hive-serde-2.3.8.jar
[SPARK-33525][SQL] Update hive-service-rpc to 3.1.2 ### What changes were proposed in this pull request? We supported Hive metastore are 0.12.0 through 3.1.2, but we supported hive-jdbc are 0.12.0 through 2.3.7. It will throw `TProtocolException` if we use hive-jdbc 3.x: ``` [rootspark-3267648 apache-hive-3.1.2-bin]# bin/beeline -u jdbc:hive2://localhost:10000/default Connecting to jdbc:hive2://localhost:10000/default Connected to: Spark SQL (version 3.1.0-SNAPSHOT) Driver: Hive JDBC (version 3.1.2) Transaction isolation: TRANSACTION_REPEATABLE_READ Beeline version 3.1.2 by Apache Hive 0: jdbc:hive2://localhost:10000/default> create table t1(id int) using parquet; Unexpected end of file when reading from HS2 server. The root cause might be too many concurrent connections. Please ask the administrator to check the number of active connections, and adjust hive.server2.thrift.max.worker.threads if applicable. Error: org.apache.thrift.transport.TTransportException (state=08S01,code=0) ``` ``` org.apache.thrift.protocol.TProtocolException: Missing version in readMessageBegin, old client? at org.apache.thrift.protocol.TBinaryProtocol.readMessageBegin(TBinaryProtocol.java:234) at org.apache.thrift.TBaseProcessor.process(TBaseProcessor.java:27) at org.apache.hive.service.auth.TSetIpAddressProcessor.process(TSetIpAddressProcessor.java:53) at org.apache.thrift.server.TThreadPoolServer$WorkerProcess.run(TThreadPoolServer.java:310) at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1130) at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:630) at java.base/java.lang.Thread.run(Thread.java:832) ``` This pr upgrade hive-service-rpc to 3.1.2 to fix this issue. ### Why are the changes needed? To support hive-jdbc 3.x. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Manual test: ``` [rootspark-3267648 apache-hive-3.1.2-bin]# bin/beeline -u jdbc:hive2://localhost:10000/default Connecting to jdbc:hive2://localhost:10000/default Connected to: Spark SQL (version 3.1.0-SNAPSHOT) Driver: Hive JDBC (version 3.1.2) Transaction isolation: TRANSACTION_REPEATABLE_READ Beeline version 3.1.2 by Apache Hive 0: jdbc:hive2://localhost:10000/default> create table t1(id int) using parquet; +---------+ | Result | +---------+ +---------+ No rows selected (1.051 seconds) 0: jdbc:hive2://localhost:10000/default> insert into t1 values(1); +---------+ | Result | +---------+ +---------+ No rows selected (2.08 seconds) 0: jdbc:hive2://localhost:10000/default> select * from t1; +-----+ | id | +-----+ | 1 | +-----+ 1 row selected (0.605 seconds) ``` Closes #30478 from wangyum/SPARK-33525. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
2020-11-25 15:37:59 -05:00
hive-service-rpc/3.1.2//hive-service-rpc-3.1.2.jar
hive-shims-0.23/2.3.8//hive-shims-0.23-2.3.8.jar
hive-shims-common/2.3.8//hive-shims-common-2.3.8.jar
hive-shims-scheduler/2.3.8//hive-shims-scheduler-2.3.8.jar
hive-shims/2.3.8//hive-shims-2.3.8.jar
hive-storage-api/2.7.2//hive-storage-api-2.7.2.jar
hive-vector-code-gen/2.3.8//hive-vector-code-gen-2.3.8.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
hk2-api/2.6.1//hk2-api-2.6.1.jar
hk2-locator/2.6.1//hk2-locator-2.6.1.jar
hk2-utils/2.6.1//hk2-utils-2.6.1.jar
htrace-core/3.1.0-incubating//htrace-core-3.1.0-incubating.jar
httpclient/4.5.13//httpclient-4.5.13.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
httpcore/4.4.12//httpcore-4.4.12.jar
istack-commons-runtime/3.0.8//istack-commons-runtime-3.0.8.jar
ivy/2.4.0//ivy-2.4.0.jar
jackson-annotations/2.11.4//jackson-annotations-2.11.4.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
jackson-core-asl/1.9.13//jackson-core-asl-1.9.13.jar
jackson-core/2.11.4//jackson-core-2.11.4.jar
jackson-databind/2.11.4//jackson-databind-2.11.4.jar
jackson-dataformat-yaml/2.11.4//jackson-dataformat-yaml-2.11.4.jar
jackson-datatype-jsr310/2.11.2//jackson-datatype-jsr310-2.11.2.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
jackson-jaxrs/1.9.13//jackson-jaxrs-1.9.13.jar
jackson-mapper-asl/1.9.13//jackson-mapper-asl-1.9.13.jar
jackson-module-jaxb-annotations/2.11.4//jackson-module-jaxb-annotations-2.11.4.jar
jackson-module-paranamer/2.11.4//jackson-module-paranamer-2.11.4.jar
jackson-module-scala_2.12/2.11.4//jackson-module-scala_2.12-2.11.4.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
jackson-xc/1.9.13//jackson-xc-1.9.13.jar
jakarta.activation-api/1.2.1//jakarta.activation-api-1.2.1.jar
jakarta.annotation-api/1.3.5//jakarta.annotation-api-1.3.5.jar
jakarta.inject/2.6.1//jakarta.inject-2.6.1.jar
[SPARK-33705][SQL][TEST] Fix HiveThriftHttpServerSuite flakiness ### What changes were proposed in this pull request? TO FIX flaky tests: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/132345/testReport/ ``` org.apache.spark.sql.hive.thriftserver.HiveThriftHttpServerSuite.JDBC query execution org.apache.spark.sql.hive.thriftserver.HiveThriftHttpServerSuite.Checks Hive version org.apache.spark.sql.hive.thriftserver.HiveThriftHttpServerSuite.SPARK-24829 Checks cast as float ``` The root cause here is a jar conflict issue. `NewCookie.isHttpOnly` is not defined in the `jsr311-api.jar` which conflicts The transitive artifact `jsr311-api.jar` of `hadoop-client` is excluded at the maven side. See https://issues.apache.org/jira/browse/SPARK-27179. The Jenkins PR builder and Github Action use `SBT` as the compiler tool. First, the exclusion rule from maven is not followed by sbt, so I was able to see `jsr311-api.jar` from maven cache to be added to the classpath directly. **This seems to be a bug of `sbt-pom-reader` plugin but I'm not that sure.** Then I added an `ExcludeRule` for the `hive-thriftserver` module at the SBT side and did see the `jsr311-api.jar` gone, but the CI jobs still failed with the same error. I added a trace log in ThriftHttpServlet ```s ERROR ThriftHttpServlet: !!!!!!!!! Suspect???????? ---> file:/home/jenkins/workspace/SparkPullRequestBuilder/assembly/target/scala-2.12/jars/jsr311-api-1.1.1.jar ``` And the log pointed out that the assembly phase copied it to `assembly/target/scala-2.12/jars/` which will be added to the classpath too. With the help of SBT `dependencyTree` tool, I saw the `jsr311-api` again as a transitive of `jersery-core` from `yarn` module with a `test` scope. So **This seems to be another bug from the SBT side of the `sbt-assembly` plugin.** It copied a test scope transitive artifact to the assembly output. In this PR, I defined some rules in SparkBuild.scala to bypass the potential bugs from the SBT side. First, exclude the `jsr311` from all over the project and then add it back separately to the YARN module for SBT. Additionally, the HiveThriftServerSuites was reflected for reducing flakiness too, but not related to the bugs I have found so far. ### Why are the changes needed? fix test here ### Does this PR introduce _any_ user-facing change? NO ### How was this patch tested? passing jenkins and ga Closes #30643 from yaooqinn/HiveThriftHttpServerSuite. Authored-by: Kent Yao <yaooqinn@hotmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-14 00:14:38 -05:00
jakarta.servlet-api/4.0.3//jakarta.servlet-api-4.0.3.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
jakarta.validation-api/2.0.2//jakarta.validation-api-2.0.2.jar
jakarta.ws.rs-api/2.1.6//jakarta.ws.rs-api-2.1.6.jar
jakarta.xml.bind-api/2.3.2//jakarta.xml.bind-api-2.3.2.jar
janino/3.0.16//janino-3.0.16.jar
javassist/3.25.0-GA//javassist-3.25.0-GA.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
javax.inject/1//javax.inject-1.jar
javax.jdo/3.2.0-m3//javax.jdo-3.2.0-m3.jar
javolution/5.5.1//javolution-5.5.1.jar
[SPARK-33212][BUILD] Upgrade to Hadoop 3.2.2 and move to shaded clients for Hadoop 3.x profile ### What changes were proposed in this pull request? This: 1. switches Spark to use shaded Hadoop clients, namely hadoop-client-api and hadoop-client-runtime, for Hadoop 3.x. 2. upgrade built-in version for Hadoop 3.x to Hadoop 3.2.2 Note that for Hadoop 2.7, we'll still use the same modules such as hadoop-client. In order to still keep default Hadoop profile to be hadoop-3.2, this defines the following Maven properties: ``` hadoop-client-api.artifact hadoop-client-runtime.artifact hadoop-client-minicluster.artifact ``` which default to: ``` hadoop-client-api hadoop-client-runtime hadoop-client-minicluster ``` but all switch to `hadoop-client` when the Hadoop profile is hadoop-2.7. A side affect from this is we'll import the same dependency multiple times. For this I have to disable Maven enforcer `banDuplicatePomDependencyVersions`. Besides above, there are the following changes: - explicitly add a few dependencies which are imported via transitive dependencies from Hadoop jars, but are removed from the shaded client jars. - removed the use of `ProxyUriUtils.getPath` from `ApplicationMaster` which is a server-side/private API. - modified `IsolatedClientLoader` to exclude `hadoop-auth` jars when Hadoop version is 3.x. This change should only matter when we're not sharing Hadoop classes with Spark (which is _mostly_ used in tests). ### Why are the changes needed? Hadoop 3.2.2 is released with new features and bug fixes, so it's good for the Spark community to adopt it. However, latest Hadoop versions starting from Hadoop 3.2.1 have upgraded to use Guava 27+. In order to resolve Guava conflicts, this takes the approach by switching to shaded client jars provided by Hadoop. This also has the benefits of avoid pulling other 3rd party dependencies from Hadoop side so as to avoid more potential future conflicts. ### Does this PR introduce _any_ user-facing change? When people use Spark with `hadoop-provided` option, they should make sure class path contains `hadoop-client-api` and `hadoop-client-runtime` jars. In addition, they may need to make sure these jars appear before other Hadoop jars in the order. Otherwise, classes may be loaded from the other non-shaded Hadoop jars and cause potential conflicts. ### How was this patch tested? Relying on existing tests. Closes #30701 from sunchao/test-hadoop-3.2.2. Authored-by: Chao Sun <sunchao@apple.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-15 17:06:50 -05:00
jaxb-api/2.2.11//jaxb-api-2.2.11.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
jaxb-runtime/2.3.2//jaxb-runtime-2.3.2.jar
jcl-over-slf4j/1.7.30//jcl-over-slf4j-1.7.30.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
jdo-api/3.0.1//jdo-api-3.0.1.jar
jersey-client/2.30//jersey-client-2.30.jar
jersey-common/2.30//jersey-common-2.30.jar
jersey-container-servlet-core/2.30//jersey-container-servlet-core-2.30.jar
jersey-container-servlet/2.30//jersey-container-servlet-2.30.jar
jersey-hk2/2.30//jersey-hk2-2.30.jar
jersey-media-jaxb/2.30//jersey-media-jaxb-2.30.jar
jersey-server/2.30//jersey-server-2.30.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
jetty-sslengine/6.1.26//jetty-sslengine-6.1.26.jar
jetty-util/6.1.26//jetty-util-6.1.26.jar
jetty/6.1.26//jetty-6.1.26.jar
jline/2.14.6//jline-2.14.6.jar
joda-time/2.10.5//joda-time-2.10.5.jar
jodd-core/3.5.2//jodd-core-3.5.2.jar
jpam/1.1//jpam-1.1.jar
json/1.8//json-1.8.jar
[SPARK-32441][BUILD][CORE] Update json4s to 3.7.0-M5 for Scala 2.13 ### What changes were proposed in this pull request? This PR aims to upgrade `json4s` to from 3.6.6 to 3.7.0-M5 for Scala 2.13 support at Apache Spark 3.1.0 on December. We will upgrade to the latest `json4s` around November. ### Why are the changes needed? `json4s` starts to support Scala 2.13 since v3.7.0-M4. - https://github.com/json4s/json4s/issues/660 - https://github.com/json4s/json4s/commit/b013af8e757ee15c15a6a1f19c672f7e7044a868 Old `json4s` causes many UT failures with `NoSuchMethodException`. ```scala Cause: java.lang.NoSuchMethodException: scala.collection.immutable.Seq$.apply(scala.collection.Seq) at java.lang.Class.getMethod(Class.java:1786) ``` The following is one example. ```scala $ dev/change-scala-version.sh 2.13 $ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.executor.CoarseGrainedExecutorBackendSuite ... Tests: succeeded 4, failed 9, canceled 0, ignored 0, pending 0 *** 9 TESTS FAILED *** ``` ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? 1. **Scala 2.12**: Pass the Jenkins or GitHub Action with the existing tests. 2. **Scala 2.13**: Do the following manually at least. ```scala $ dev/change-scala-version.sh 2.13 $ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.executor.CoarseGrainedExecutorBackendSuite ... Tests: succeeded 13, failed 0, canceled 0, ignored 0, pending 0 All tests passed. ``` Closes #29239 from dongjoon-hyun/SPARK-32441. Authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
2020-07-25 23:34:31 -04:00
json4s-ast_2.12/3.7.0-M5//json4s-ast_2.12-3.7.0-M5.jar
json4s-core_2.12/3.7.0-M5//json4s-core_2.12-3.7.0-M5.jar
json4s-jackson_2.12/3.7.0-M5//json4s-jackson_2.12-3.7.0-M5.jar
json4s-scalap_2.12/3.7.0-M5//json4s-scalap_2.12-3.7.0-M5.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
jsp-api/2.1//jsp-api-2.1.jar
jsr305/3.0.0//jsr305-3.0.0.jar
jta/1.1//jta-1.1.jar
jul-to-slf4j/1.7.30//jul-to-slf4j-1.7.30.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
kryo-shaded/4.0.2//kryo-shaded-4.0.2.jar
[SPARK-34486][K8S] Upgrade kubernetes-client to 4.13.2 ### What changes were proposed in this pull request? This PR aims to upgrade `kubernetes-client` library from 4.12.0 to 4.13.2 for Apache Spark 3.2.0. ### Why are the changes needed? This will bring [K8s 1.19.1](https://github.com/fabric8io/kubernetes-client/pull/2541) models officially and the latest bug fixes. - https://github.com/fabric8io/kubernetes-client/releases/tag/v4.13.0 - https://github.com/fabric8io/kubernetes-client/releases/tag/v4.13.1 - https://github.com/fabric8io/kubernetes-client/releases/tag/v4.13.2 ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Pass the K8s IT and UT. ``` KubernetesSuite: - Run SparkPi with no resources - Run SparkPi with a very long application name. - Use SparkLauncher.NO_RESOURCE - Run SparkPi with a master URL without a scheme. - Run SparkPi with an argument. - Run SparkPi with custom labels, annotations, and environment variables. - All pods have the same service account by default - Run extraJVMOptions check on driver - Run SparkRemoteFileTest using a remote data file - Verify logging configuration is picked from the provided SPARK_CONF_DIR/log4j.properties - Run SparkPi with env and mount secrets. - Run PySpark on simple pi.py example - Run PySpark to test a pyfiles example - Run PySpark with memory customization - Run in client mode. - Start pod creation from template - PVs with local storage - Launcher client dependencies - SPARK-33615: Launcher client archives - SPARK-33748: Launcher python client respecting PYSPARK_PYTHON - SPARK-33748: Launcher python client respecting spark.pyspark.python and spark.pyspark.driver.python - Launcher python client dependencies using a zip file - Test basic decommissioning - Test basic decommissioning with shuffle cleanup - Test decommissioning with dynamic allocation & shuffle cleanups - Test decommissioning timeouts - Run SparkR on simple dataframe.R example Run completed in 19 minutes, 25 seconds. Total number of tests run: 27 Suites: completed 2, aborted 0 Tests: succeeded 27, failed 0, canceled 0, ignored 0, pending 0 All tests passed. ``` Closes #31602 from dongjoon-hyun/SPARK-34486. Authored-by: Dongjoon Hyun <dhyun@apple.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2021-02-21 04:35:38 -05:00
kubernetes-client/4.13.2//kubernetes-client-4.13.2.jar
kubernetes-model-admissionregistration/4.13.2//kubernetes-model-admissionregistration-4.13.2.jar
kubernetes-model-apiextensions/4.13.2//kubernetes-model-apiextensions-4.13.2.jar
kubernetes-model-apps/4.13.2//kubernetes-model-apps-4.13.2.jar
kubernetes-model-autoscaling/4.13.2//kubernetes-model-autoscaling-4.13.2.jar
kubernetes-model-batch/4.13.2//kubernetes-model-batch-4.13.2.jar
kubernetes-model-certificates/4.13.2//kubernetes-model-certificates-4.13.2.jar
kubernetes-model-common/4.13.2//kubernetes-model-common-4.13.2.jar
kubernetes-model-coordination/4.13.2//kubernetes-model-coordination-4.13.2.jar
kubernetes-model-core/4.13.2//kubernetes-model-core-4.13.2.jar
kubernetes-model-discovery/4.13.2//kubernetes-model-discovery-4.13.2.jar
kubernetes-model-events/4.13.2//kubernetes-model-events-4.13.2.jar
kubernetes-model-extensions/4.13.2//kubernetes-model-extensions-4.13.2.jar
kubernetes-model-metrics/4.13.2//kubernetes-model-metrics-4.13.2.jar
kubernetes-model-networking/4.13.2//kubernetes-model-networking-4.13.2.jar
kubernetes-model-node/4.13.2//kubernetes-model-node-4.13.2.jar
kubernetes-model-policy/4.13.2//kubernetes-model-policy-4.13.2.jar
kubernetes-model-rbac/4.13.2//kubernetes-model-rbac-4.13.2.jar
kubernetes-model-scheduling/4.13.2//kubernetes-model-scheduling-4.13.2.jar
kubernetes-model-settings/4.13.2//kubernetes-model-settings-4.13.2.jar
kubernetes-model-storageclass/4.13.2//kubernetes-model-storageclass-4.13.2.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
leveldbjni-all/1.8//leveldbjni-all-1.8.jar
libfb303/0.9.3//libfb303-0.9.3.jar
libthrift/0.12.0//libthrift-0.12.0.jar
log4j/1.2.17//log4j-1.2.17.jar
logging-interceptor/3.12.12//logging-interceptor-3.12.12.jar
lz4-java/1.7.1//lz4-java-1.7.1.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
machinist_2.12/0.6.8//machinist_2.12-0.6.8.jar
macro-compat_2.12/1.1.1//macro-compat_2.12-1.1.1.jar
mesos/1.4.0/shaded-protobuf/mesos-1.4.0-shaded-protobuf.jar
metrics-core/4.1.1//metrics-core-4.1.1.jar
metrics-graphite/4.1.1//metrics-graphite-4.1.1.jar
metrics-jmx/4.1.1//metrics-jmx-4.1.1.jar
metrics-json/4.1.1//metrics-json-4.1.1.jar
metrics-jvm/4.1.1//metrics-jvm-4.1.1.jar
minlog/1.3.0//minlog-1.3.0.jar
netty-all/4.1.51.Final//netty-all-4.1.51.Final.jar
objenesis/2.6//objenesis-2.6.jar
okhttp/3.12.12//okhttp-3.12.12.jar
okio/1.14.0//okio-1.14.0.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
opencsv/2.3//opencsv-2.3.jar
orc-core/1.6.7//orc-core-1.6.7.jar
orc-mapreduce/1.6.7//orc-mapreduce-1.6.7.jar
orc-shims/1.6.7//orc-shims-1.6.7.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
oro/2.0.8//oro-2.0.8.jar
osgi-resource-locator/1.0.3//osgi-resource-locator-1.0.3.jar
paranamer/2.8//paranamer-2.8.jar
parquet-column/1.11.1//parquet-column-1.11.1.jar
parquet-common/1.11.1//parquet-common-1.11.1.jar
parquet-encoding/1.11.1//parquet-encoding-1.11.1.jar
parquet-format-structures/1.11.1//parquet-format-structures-1.11.1.jar
parquet-hadoop/1.11.1//parquet-hadoop-1.11.1.jar
parquet-jackson/1.11.1//parquet-jackson-1.11.1.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
protobuf-java/2.5.0//protobuf-java-2.5.0.jar
py4j/0.10.9.1//py4j-0.10.9.1.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
pyrolite/4.30//pyrolite-4.30.jar
scala-collection-compat_2.12/2.1.1//scala-collection-compat_2.12-2.1.1.jar
scala-compiler/2.12.10//scala-compiler-2.12.10.jar
scala-library/2.12.10//scala-library-2.12.10.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
scala-parser-combinators_2.12/1.1.2//scala-parser-combinators_2.12-1.1.2.jar
scala-reflect/2.12.10//scala-reflect-2.12.10.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
scala-xml_2.12/1.2.0//scala-xml_2.12-1.2.0.jar
shapeless_2.12/2.3.3//shapeless_2.12-2.3.3.jar
shims/0.9.0//shims-0.9.0.jar
slf4j-api/1.7.30//slf4j-api-1.7.30.jar
slf4j-log4j12/1.7.30//slf4j-log4j12-1.7.30.jar
snakeyaml/1.26//snakeyaml-1.26.jar
snappy-java/1.1.8.2//snappy-java-1.1.8.2.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
spire-macros_2.12/0.17.0-M1//spire-macros_2.12-0.17.0-M1.jar
spire-platform_2.12/0.17.0-M1//spire-platform_2.12-0.17.0-M1.jar
spire-util_2.12/0.17.0-M1//spire-util_2.12-0.17.0-M1.jar
spire_2.12/0.17.0-M1//spire_2.12-0.17.0-M1.jar
stax-api/1.0.1//stax-api-1.0.1.jar
stream/2.9.6//stream-2.9.6.jar
super-csv/2.2.0//super-csv-2.2.0.jar
threeten-extra/1.5.0//threeten-extra-1.5.0.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
transaction-api/1.1//transaction-api-1.1.jar
univocity-parsers/2.9.1//univocity-parsers-2.9.1.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
velocity/1.5//velocity-1.5.jar
xbean-asm7-shaded/4.15//xbean-asm7-shaded-4.15.jar
xercesImpl/2.12.0//xercesImpl-2.12.0.jar
[SPARK-30994][BUILD][FOLLOW-UP] Change scope of xml-apis to include it and add xerces in SBT as dependency override ### What changes were proposed in this pull request? This PR propose 1. Explicitly include xml-apis. xml-apis is already the part of xerces 2.12.0 (https://repo1.maven.org/maven2/xerces/xercesImpl/2.12.0/xercesImpl-2.12.0.pom). However, we're excluding it by setting `scope` to `test`. This seems causing `spark-shell`, built from Maven, to fail. Seems like previously xml-apis wasn't reached for some reasons but after we upgrade, it seems requiring. Therefore, this PR proposes to include it. 2. Pins `xerces` version in SBT as well. Seems this dependency is resolved differently from Maven. Note that Hadoop 3 does not looks requiring this as they replaced xerces as of [HDFS-12221](https://issues.apache.org/jira/browse/HDFS-12221). ### Why are the changes needed? To make `spark-shell` working from Maven build, and uses the same xerces version. ### Does this PR introduce any user-facing change? No, it's master only. ### How was this patch tested? **1.** ```bash ./build/mvn -DskipTests -Psparkr -Phive clean package ./bin/spark-shell ``` Before: ``` Exception in thread "main" java.lang.NoClassDefFoundError: org/w3c/dom/ElementTraversal at java.lang.ClassLoader.defineClass1(Native Method) at java.lang.ClassLoader.defineClass(ClassLoader.java:763) at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142) at java.net.URLClassLoader.defineClass(URLClassLoader.java:468) at java.net.URLClassLoader.access$100(URLClassLoader.java:74) at java.net.URLClassLoader$1.run(URLClassLoader.java:369) at java.net.URLClassLoader$1.run(URLClassLoader.java:363) at java.security.AccessController.doPrivileged(Native Method) at java.net.URLClassLoader.findClass(URLClassLoader.java:362) at java.lang.ClassLoader.loadClass(ClassLoader.java:424) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349) at java.lang.ClassLoader.loadClass(ClassLoader.java:357) at org.apache.xerces.parsers.AbstractDOMParser.startDocument(Unknown Source) at org.apache.xerces.xinclude.XIncludeHandler.startDocument(Unknown Source) at org.apache.xerces.impl.dtd.XMLDTDValidator.startDocument(Unknown Source) at org.apache.xerces.impl.XMLDocumentScannerImpl.startEntity(Unknown Source) at org.apache.xerces.impl.XMLVersionDetector.startDocumentParsing(Unknown Source) at org.apache.xerces.parsers.XML11Configuration.parse(Unknown Source) at org.apache.xerces.parsers.XML11Configuration.parse(Unknown Source) at org.apache.xerces.parsers.XMLParser.parse(Unknown Source) at org.apache.xerces.parsers.DOMParser.parse(Unknown Source) at org.apache.xerces.jaxp.DocumentBuilderImpl.parse(Unknown Source) at javax.xml.parsers.DocumentBuilder.parse(DocumentBuilder.java:150) at org.apache.hadoop.conf.Configuration.parse(Configuration.java:2482) at org.apache.hadoop.conf.Configuration.parse(Configuration.java:2470) at org.apache.hadoop.conf.Configuration.loadResource(Configuration.java:2541) at org.apache.hadoop.conf.Configuration.loadResources(Configuration.java:2494) at org.apache.hadoop.conf.Configuration.getProps(Configuration.java:2407) at org.apache.hadoop.conf.Configuration.set(Configuration.java:1143) at org.apache.hadoop.conf.Configuration.set(Configuration.java:1115) at org.apache.spark.deploy.SparkHadoopUtil$.org$apache$spark$deploy$SparkHadoopUtil$$appendS3AndSparkHadoopHiveConfigurations(SparkHadoopUtil.scala:456) at org.apache.spark.deploy.SparkHadoopUtil$.newConfiguration(SparkHadoopUtil.scala:427) at org.apache.spark.deploy.SparkSubmit.$anonfun$prepareSubmitEnvironment$2(SparkSubmit.scala:342) at scala.Option.getOrElse(Option.scala:189) at org.apache.spark.deploy.SparkSubmit.prepareSubmitEnvironment(SparkSubmit.scala:342) at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:871) at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180) at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203) at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90) at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1007) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1016) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) Caused by: java.lang.ClassNotFoundException: org.w3c.dom.ElementTraversal at java.net.URLClassLoader.findClass(URLClassLoader.java:382) at java.lang.ClassLoader.loadClass(ClassLoader.java:424) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349) at java.lang.ClassLoader.loadClass(ClassLoader.java:357) ... 42 more ``` After: ``` ... Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /___/ .__/\_,_/_/ /_/\_\ version 3.1.0-SNAPSHOT /_/ Using Scala version 2.12.10 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_202) Type in expressions to have them evaluated. Type :help for more information. scala> ``` **2.** ``` ./build/sbt dependencyTree -Phadoop-2.7 -Phive-2.3 -Phive-thriftserver -Phive ./build/sbt dependencyTree -Phadoop-3.2 -Phive-2.3 -Phive-thriftserver -Phive ``` Closes #27808 from HyukjinKwon/SPARK-30994. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-03-05 19:39:02 -05:00
xml-apis/1.4.01//xml-apis-1.4.01.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
xmlenc/0.52//xmlenc-0.52.jar
xz/1.8//xz-1.8.jar
[SPARK-30491][INFRA] Enable dependency audit files to tell dependency classifier ### What changes were proposed in this pull request? Enable dependency audit files to tell the value of artifact id, version, and classifier of a dependency. For example, `avro-mapred-1.8.2-hadoop2.jar` should be expanded to `avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar` where `avro-mapred` is the artifact id, `1.8.2` is the version, and `haddop2` is the classifier. ### Why are the changes needed? Dependency audit files are expected to be consumed by automated tests or downstream tools. However, current dependency audit files under `dev/deps` only show jar names. And there isn't a simple rule on how to parse the jar name to get the values of different fields. For example, `hadoop2` is the classifier of `avro-mapred-1.8.2-hadoop2.jar`, in contrast, `incubating` is the version of `htrace-core-3.1.0-incubating.jar`. Reference: There is a good example of the downstream tool that would be enabled as yhuai suggested, > Say we have a Spark application that depends on a third-party dependency `foo`, which pulls in `jackson` as a transient dependency. Unfortunately, `foo` depends on a different version of `jackson` than Spark. So, in the pom of this Spark application, we use the dependency management section to pin the version of `jackson`. By doing this, we are lifting `jackson` to the top-level dependency of my application and I want to have a way to keep tracking what Spark uses. What we can do is to cross-check my Spark application's classpath with what Spark uses. Then, with a test written in my code base, whenever my application bumps Spark version, this test will check what we define in the application and what Spark has, and then remind us to change our application's pom if needed. In my case, I am fine to directly access git to get these audit files. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? Code changes are verified by generated dependency audit files naturally. Thus, there are no tests added. Closes #27177 from mengCareers/depsOptimize. Lead-authored-by: Xinrong Meng <meng.careers@gmail.com> Co-authored-by: mengCareers <meng.careers@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-01-15 23:19:44 -05:00
zjsonpatch/0.3.0//zjsonpatch-0.3.0.jar
[SPARK-34110][BUILD] Upgrade Zookeeper to 3.6.2 ### What changes were proposed in this pull request? This PR upgrade Zookeeper to 3.6.2. ### Why are the changes needed? To make Spark running on jdk 14, otherwise: ``` 21/01/13 20:25:32,533 WARN [Driver-SendThread(apache-spark-zk-3.vip.hadoop.com:2181)] zookeeper.ClientCnxn:1164 : Session 0x0 for server apache-spark-zk-3.vip.hadoop.com/<unresolved>:2181, unexpected error, closing socket connection and attempting reconnect java.lang.IllegalArgumentException: Unable to canonicalize address apache-spark-zk-3.vip.hadoop.com/<unresolved>:2181 because it's not resolvable at org.apache.zookeeper.SaslServerPrincipal.getServerPrincipal(SaslServerPrincipal.java:65) at org.apache.zookeeper.SaslServerPrincipal.getServerPrincipal(SaslServerPrincipal.java:41) at org.apache.zookeeper.ClientCnxn$SendThread.startConnect(ClientCnxn.java:1001) at org.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1060) ``` Please see [ZOOKEEPER-3779](https://issues.apache.org/jira/browse/ZOOKEEPER-3779) for more details. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Manual test: 1. Replace zookeeper-3.4.14.jar with zookeeper-3.6.2.jar and zookeeper-jute-3.6.2.jar 2. Run Spark on jdk 14. Hadoop 2.7 with HADOOP-12760, Hive 1.2.1 and Zookeeper server version is 3.4.6. Some key configurations: ``` # spark-defaults.conf spark.yarn.appMasterEnv.JAVA_HOME /apache/releases/jdk-14.0.2 spark.executorEnv.JAVA_HOME /apache/releases/jdk-14.0.2 # spark-env.sh export JAVA_HOME=/apache/releases/jdk-14.0.2 ``` Jenkins Tests - Hadoop 3.2: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/134048/testReport - Hadoop 2.7: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/134063/testReport Closes #31177 from wangyum/SPARK-34110. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-16 00:12:41 -05:00
zookeeper-jute/3.6.2//zookeeper-jute-3.6.2.jar
zookeeper/3.6.2//zookeeper-3.6.2.jar
zstd-jni/1.4.9-1//zstd-jni-1.4.9-1.jar