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/0.10//aircompressor-0.10.jar
algebra_2.12/2.0.0-M2//algebra_2.12-2.0.0-M2.jar
antlr-runtime/3.5.2//antlr-runtime-3.5.2.jar
antlr4-runtime/4.7.1//antlr4-runtime-4.7.1.jar
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/1.8.2//avro-ipc-1.8.2.jar
avro-mapred/1.8.2/hadoop2/avro-mapred-1.8.2-hadoop2.jar
avro/1.8.2//avro-1.8.2.jar
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/1.10//commons-codec-1.10.jar
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-lang3/3.10//commons-lang3-3.10.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
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/10.12.1.1//derby-10.12.1.1.jar
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
[SPARK-31381][SPARK-29245][SQL] Upgrade built-in Hive 2.3.6 to 2.3.7 ### What changes were proposed in this pull request? **Hive 2.3.7** fixed these issues: - HIVE-21508: ClassCastException when initializing HiveMetaStoreClient on JDK10 or newer - HIVE-21980:Parsing time can be high in case of deeply nested subqueries - HIVE-22249: Support Parquet through HCatalog ### Why are the changes needed? Fix CCE during creating HiveMetaStoreClient in JDK11 environment: [SPARK-29245](https://issues.apache.org/jira/browse/SPARK-29245). ### Does this PR introduce any user-facing change? No. ### How was this patch tested? - [x] Test Jenkins with Hadoop 2.7 (https://github.com/apache/spark/pull/28148#issuecomment-616757840) - [x] Test Jenkins with Hadoop 3.2 on JDK11 (https://github.com/apache/spark/pull/28148#issuecomment-616294353) - [x] Manual test with remote hive metastore. Hive side: ``` export JAVA_HOME=/usr/lib/jdk1.8.0_221 export PATH=$JAVA_HOME/bin:$PATH cd /usr/lib/hive-2.3.6 # Start Hive metastore with Hive 2.3.6 bin/schematool -dbType derby -initSchema --verbose bin/hive --service metastore ``` Spark side: ``` export JAVA_HOME=/usr/lib/jdk-11.0.3 export PATH=$JAVA_HOME/bin:$PATH build/sbt clean package -Phive -Phadoop-3.2 -Phive-thriftserver export SPARK_PREPEND_CLASSES=true bin/spark-sql --conf spark.hadoop.hive.metastore.uris=thrift://localhost:9083 ``` Closes #28148 from wangyum/SPARK-31381. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
2020-04-20 16:38:24 -04:00
hive-beeline/2.3.7//hive-beeline-2.3.7.jar
hive-cli/2.3.7//hive-cli-2.3.7.jar
hive-common/2.3.7//hive-common-2.3.7.jar
hive-exec/2.3.7/core/hive-exec-2.3.7-core.jar
hive-jdbc/2.3.7//hive-jdbc-2.3.7.jar
hive-llap-common/2.3.7//hive-llap-common-2.3.7.jar
hive-metastore/2.3.7//hive-metastore-2.3.7.jar
hive-serde/2.3.7//hive-serde-2.3.7.jar
hive-service-rpc/2.3.7//hive-service-rpc-2.3.7.jar
[SPARK-31381][SPARK-29245][SQL] Upgrade built-in Hive 2.3.6 to 2.3.7 ### What changes were proposed in this pull request? **Hive 2.3.7** fixed these issues: - HIVE-21508: ClassCastException when initializing HiveMetaStoreClient on JDK10 or newer - HIVE-21980:Parsing time can be high in case of deeply nested subqueries - HIVE-22249: Support Parquet through HCatalog ### Why are the changes needed? Fix CCE during creating HiveMetaStoreClient in JDK11 environment: [SPARK-29245](https://issues.apache.org/jira/browse/SPARK-29245). ### Does this PR introduce any user-facing change? No. ### How was this patch tested? - [x] Test Jenkins with Hadoop 2.7 (https://github.com/apache/spark/pull/28148#issuecomment-616757840) - [x] Test Jenkins with Hadoop 3.2 on JDK11 (https://github.com/apache/spark/pull/28148#issuecomment-616294353) - [x] Manual test with remote hive metastore. Hive side: ``` export JAVA_HOME=/usr/lib/jdk1.8.0_221 export PATH=$JAVA_HOME/bin:$PATH cd /usr/lib/hive-2.3.6 # Start Hive metastore with Hive 2.3.6 bin/schematool -dbType derby -initSchema --verbose bin/hive --service metastore ``` Spark side: ``` export JAVA_HOME=/usr/lib/jdk-11.0.3 export PATH=$JAVA_HOME/bin:$PATH build/sbt clean package -Phive -Phadoop-3.2 -Phive-thriftserver export SPARK_PREPEND_CLASSES=true bin/spark-sql --conf spark.hadoop.hive.metastore.uris=thrift://localhost:9083 ``` Closes #28148 from wangyum/SPARK-31381. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
2020-04-20 16:38:24 -04:00
hive-shims-0.23/2.3.7//hive-shims-0.23-2.3.7.jar
hive-shims-common/2.3.7//hive-shims-common-2.3.7.jar
hive-shims-scheduler/2.3.7//hive-shims-scheduler-2.3.7.jar
hive-shims/2.3.7//hive-shims-2.3.7.jar
hive-storage-api/2.7.2//hive-storage-api-2.7.2.jar
[SPARK-31381][SPARK-29245][SQL] Upgrade built-in Hive 2.3.6 to 2.3.7 ### What changes were proposed in this pull request? **Hive 2.3.7** fixed these issues: - HIVE-21508: ClassCastException when initializing HiveMetaStoreClient on JDK10 or newer - HIVE-21980:Parsing time can be high in case of deeply nested subqueries - HIVE-22249: Support Parquet through HCatalog ### Why are the changes needed? Fix CCE during creating HiveMetaStoreClient in JDK11 environment: [SPARK-29245](https://issues.apache.org/jira/browse/SPARK-29245). ### Does this PR introduce any user-facing change? No. ### How was this patch tested? - [x] Test Jenkins with Hadoop 2.7 (https://github.com/apache/spark/pull/28148#issuecomment-616757840) - [x] Test Jenkins with Hadoop 3.2 on JDK11 (https://github.com/apache/spark/pull/28148#issuecomment-616294353) - [x] Manual test with remote hive metastore. Hive side: ``` export JAVA_HOME=/usr/lib/jdk1.8.0_221 export PATH=$JAVA_HOME/bin:$PATH cd /usr/lib/hive-2.3.6 # Start Hive metastore with Hive 2.3.6 bin/schematool -dbType derby -initSchema --verbose bin/hive --service metastore ``` Spark side: ``` export JAVA_HOME=/usr/lib/jdk-11.0.3 export PATH=$JAVA_HOME/bin:$PATH build/sbt clean package -Phive -Phadoop-3.2 -Phive-thriftserver export SPARK_PREPEND_CLASSES=true bin/spark-sql --conf spark.hadoop.hive.metastore.uris=thrift://localhost:9083 ``` Closes #28148 from wangyum/SPARK-31381. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
2020-04-20 16:38:24 -04:00
hive-vector-code-gen/2.3.7//hive-vector-code-gen-2.3.7.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
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/4.5.6//httpclient-4.5.6.jar
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/2.10.0//jackson-annotations-2.10.0.jar
jackson-core-asl/1.9.13//jackson-core-asl-1.9.13.jar
jackson-core/2.10.0//jackson-core-2.10.0.jar
jackson-databind/2.10.0//jackson-databind-2.10.0.jar
jackson-dataformat-yaml/2.10.0//jackson-dataformat-yaml-2.10.0.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/2.10.0//jackson-module-jaxb-annotations-2.10.0.jar
jackson-module-paranamer/2.10.0//jackson-module-paranamer-2.10.0.jar
jackson-module-scala_2.12/2.10.0//jackson-module-scala_2.12-2.10.0.jar
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
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
javax.servlet-api/3.1.0//javax.servlet-api-3.1.0.jar
javolution/5.5.1//javolution-5.5.1.jar
[SPARK-33212][BUILD] Move to shaded clients for Hadoop 3.x profile ### What changes were proposed in this pull request? This switches Spark to use shaded Hadoop clients, namely hadoop-client-api and hadoop-client-runtime, for Hadoop 3.x. 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? This serves two purposes: - to unblock Spark from upgrading to Hadoop 3.2.2/3.3.0+. Latest Hadoop versions have upgraded to use Guava 27+ and in order to adopt the latest Hadoop versions in Spark, we'll need to resolve the Guava conflicts. This takes the approach by switching to shaded client jars provided by Hadoop. - avoid pulling 3rd party dependencies from Hadoop and avoid 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 #29843 from sunchao/SPARK-29250. Authored-by: Chao Sun <sunchao@apple.com> Signed-off-by: DB Tsai <d_tsai@apple.com>
2020-10-21 23:21:34 -04:00
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
kubernetes-client/4.11.1//kubernetes-client-4.11.1.jar
kubernetes-model-admissionregistration/4.11.1//kubernetes-model-admissionregistration-4.11.1.jar
kubernetes-model-apiextensions/4.11.1//kubernetes-model-apiextensions-4.11.1.jar
kubernetes-model-apps/4.11.1//kubernetes-model-apps-4.11.1.jar
kubernetes-model-autoscaling/4.11.1//kubernetes-model-autoscaling-4.11.1.jar
kubernetes-model-batch/4.11.1//kubernetes-model-batch-4.11.1.jar
kubernetes-model-certificates/4.11.1//kubernetes-model-certificates-4.11.1.jar
kubernetes-model-common/4.11.1//kubernetes-model-common-4.11.1.jar
kubernetes-model-coordination/4.11.1//kubernetes-model-coordination-4.11.1.jar
kubernetes-model-core/4.11.1//kubernetes-model-core-4.11.1.jar
kubernetes-model-discovery/4.11.1//kubernetes-model-discovery-4.11.1.jar
kubernetes-model-events/4.11.1//kubernetes-model-events-4.11.1.jar
kubernetes-model-extensions/4.11.1//kubernetes-model-extensions-4.11.1.jar
kubernetes-model-metrics/4.11.1//kubernetes-model-metrics-4.11.1.jar
kubernetes-model-networking/4.11.1//kubernetes-model-networking-4.11.1.jar
kubernetes-model-policy/4.11.1//kubernetes-model-policy-4.11.1.jar
kubernetes-model-rbac/4.11.1//kubernetes-model-rbac-4.11.1.jar
kubernetes-model-scheduling/4.11.1//kubernetes-model-scheduling-4.11.1.jar
kubernetes-model-settings/4.11.1//kubernetes-model-settings-4.11.1.jar
kubernetes-model-storageclass/4.11.1//kubernetes-model-storageclass-4.11.1.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
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
openshift-model/4.11.1//openshift-model-4.11.1.jar
orc-core/1.5.12//orc-core-1.5.12.jar
orc-mapreduce/1.5.12//orc-mapreduce-1.5.12.jar
orc-shims/1.5.12//orc-shims-1.5.12.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/1.10.1//parquet-column-1.10.1.jar
parquet-common/1.10.1//parquet-common-1.10.1.jar
parquet-encoding/1.10.1//parquet-encoding-1.10.1.jar
parquet-format/2.4.0//parquet-format-2.4.0.jar
parquet-hadoop/1.10.1//parquet-hadoop-1.10.1.jar
parquet-jackson/1.10.1//parquet-jackson-1.10.1.jar
protobuf-java/2.5.0//protobuf-java-2.5.0.jar
py4j/0.10.9//py4j-0.10.9.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
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
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
[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
snakeyaml/1.24//snakeyaml-1.24.jar
snappy-java/1.1.8//snappy-java-1.1.8.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
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/2.9.0//univocity-parsers-2.9.0.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
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/1.5//xz-1.5.jar
zjsonpatch/0.3.0//zjsonpatch-0.3.0.jar
zookeeper/3.4.14//zookeeper-3.4.14.jar
zstd-jni/1.4.5-6//zstd-jni-1.4.5-6.jar