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Enabled Databricks 17.3 tests and removed support for Databricks 12.2
Databricks 17.3 IT: Jenkins, POM cleanup, docs and build version updates Signed-off-by: timl <timl@nvidia.com>
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CONTRIBUTING.md

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@@ -252,12 +252,12 @@ The following acronyms may appear in directory names:
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|Acronym|Definition |Example|Example Explanation |
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|-------|------------|-------|----------------------------------------------|
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|db |Databricks |332db |Databricks Spark based on Spark 3.3.2 |
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|db |Databricks |341db |Databricks Spark based on Spark 3.4.1 |
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|cdh |Cloudera CDH|(removed)|Cloudera CDH shims have been removed |
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The version-specific directory names have one of the following forms / use cases:
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* `src/main/spark${buildver}`, example: `src/main/spark332db`
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* `src/main/spark${buildver}`, example: `src/main/spark341db`
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* `src/test/spark${buildver}`, example: `src/test/spark340`
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with a special shim descriptor as a Scala/Java comment. See [shimplify.md][1]

build/get_buildvers.py

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@@ -57,7 +57,7 @@ def _get_buildvers(buildvers, pom_file, logger=None, ignore_excluded_shims=False
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# exists. This is expected when pom.xml and scala2.13/pom.xml
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# share the same exclusion list but have different profiles due
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# to #if scala-2.12/#if scala-2.13 conditional comments
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# (e.g. 332db only in pom.xml, 400 only in scala2.13/pom.xml).
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# (e.g. profile split between pom.xml and scala2.13/pom.xml via #if scala comments).
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if logger:
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logger.debug(
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"Shim %s listed in dyn.shim.excluded.releases not found in "

delta-lake/README.md

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@@ -18,9 +18,9 @@ and directory contains the corresponding support code.
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| 2.4.x | Spark 3.4.x | `delta-24x` |
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| 3.3.x | Spark 3.5.[3-] | `delta-33x` |
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| 4.0.x | Spark 4.0.x | `delta-40x` |
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| Databricks 12.2 | Databricks 12.2 | `delta-spark332db` |
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| Databricks 13.3 | Databricks 13.3 | `delta-spark341db` |
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| Databricks 14.3 | Databricks 14.3 | `delta-spark350db143` |
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| Databricks 17.3 | Databricks 17.3 | `delta-spark400db173` |
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Delta Lake is not supported on all Spark versions, and for Spark versions where it is not

docs/dev/lore.md

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@@ -121,7 +121,6 @@ restored data to console.
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`GpuShuffleExchangeExec`), leaf operator (e.g. `GpuFileSourceScanExec`) are not supported.
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3. **GpuDataWritingCommandExec is not supported for LORE dump on certain Spark versions**.
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The following versions are not supported due to compatibility issues with `GpuWriteFiles`:
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- Spark 3.3.2 Databricks (`332db`)
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- Spark 3.4.0 (`340`)
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- Spark 3.4.1 (`341`)
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- Spark 3.4.1 Databricks (`341db`)
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- Spark 3.5.6 (`356`)
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- Spark 3.5.7 (`357`)
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- Spark 4.0.0 (`400`)
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- Spark 4.0.0 Databricks 17.3 (`400db173`)
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- Spark 4.0.1 (`401`)
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When attempting to dump a `GpuDataWritingCommandExec` on these versions, LORE will throw an

docs/download.md

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@@ -44,9 +44,9 @@ The plugin is designed to work on NVIDIA Volta, Turing, Ampere, Ada Lovelace, Ho
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Scala 2.13: Spark 3.5.0+, 4.0.0, 4.0.1, 4.0.2, 4.1.1
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Supported Databricks runtime versions for Azure and AWS:
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Databricks 12.2 ML LTS (GPU, Scala 2.12, Spark 3.3.2)
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Databricks 13.3 ML LTS (GPU, Scala 2.12, Spark 3.4.1)
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Databricks 14.3 ML LTS (GPU, Scala 2.12, Spark 3.5.0)
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Databricks 17.3 ML LTS (GPU, Scala 2.13, Spark 4.0.0)
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Supported Dataproc versions (Debian/Ubuntu/Rocky):
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GCP Dataproc 2.1

jenkins/Jenkinsfile-blossom.premerge-databricks

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@@ -93,7 +93,7 @@ pipeline {
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// 'name' and 'value' only supprt literal string in the declarative Jenkins
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// Refer to Jenkins issue https://issues.jenkins.io/browse/JENKINS-62127
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name 'DB_RUNTIME'
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values '12.2', '13.3', '14.3', '17.3'
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values '13.3', '14.3', '17.3'
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}
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}
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stages {
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}
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}
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// TODO: Temporarily skip tests on Databricks 17.3 until the test failures are fixed
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if (env.DB_RUNTIME != '17.3') {
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stage("Test agaist $SPARK_MAJOR DB") {
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dbStep = 'TEST'
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withCredentials([file(credentialsId: 'SPARK_DATABRICKS_PRIVKEY', variable: 'DATABRICKS_PRIVKEY')]) {
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def TEST_PARAMS = DbUtils.getParameters(this, dbStep, "-c $CLUSTER_ID")
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// Get built tar from the path "$testArgs" on Databricks cluster
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// Refer to https://github.com/NVIDIA/spark-rapids/pull/11788/files#diff-db28879431d57d0e454a2c7ee89fdda9abdec463c61771333d6a6565bf96c062R52-R55
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sh "python3 ./jenkins/databricks/run-tests.py $TEST_PARAMS $testArgs"
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}
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stage("Test agaist $SPARK_MAJOR DB") {
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dbStep = 'TEST'
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withCredentials([file(credentialsId: 'SPARK_DATABRICKS_PRIVKEY', variable: 'DATABRICKS_PRIVKEY')]) {
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def TEST_PARAMS = DbUtils.getParameters(this, dbStep, "-c $CLUSTER_ID")
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// Get built tar from the path "$testArgs" on Databricks cluster
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// Refer to https://github.com/NVIDIA/spark-rapids/pull/11788/files#diff-db28879431d57d0e454a2c7ee89fdda9abdec463c61771333d6a6565bf96c062R52-R55
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sh "python3 ./jenkins/databricks/run-tests.py $TEST_PARAMS $testArgs"
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}
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}
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} finally {

pom.xml

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<!-- Note Databricks requires 2 properties -Ddatabricks and -Dbuildver=3*db -->
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<!-- #if scala-2.12 -->
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<profile>
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<id>release332db</id>
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<activation>
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<property>
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<name>buildver</name>
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<value>332db</value>
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</property>
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</activation>
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<properties>
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<spark.version.classifier>spark332db</spark.version.classifier>
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<spark.version>${spark332db.version}</spark.version>
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<spark.test.version>${spark332db.version}</spark.test.version>
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<hadoop.client.version>3.3.1</hadoop.client.version>
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<rat.consoleOutput>true</rat.consoleOutput>
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<parquet.hadoop.version>1.12.0</parquet.hadoop.version>
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<rapids.delta.artifactId1>rapids-4-spark-delta-${spark.version.classifier}</rapids.delta.artifactId1>
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</properties>
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<modules>
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<module>shim-deps/databricks</module>
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<module>delta-lake/delta-spark332db</module>
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<module>iceberg/iceberg-stub</module>
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</modules>
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</profile>
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<profile>
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<id>release341db</id>
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<activation>
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<spark342.version>3.4.2</spark342.version>
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<spark343.version>3.4.3</spark343.version>
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<spark344.version>3.4.4</spark344.version>
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<spark332db.version>3.3.2-databricks</spark332db.version>
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<spark341db.version>3.4.1-databricks</spark341db.version>
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<spark350db143.version>3.5.0-databricks-143</spark350db143.version>
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<spark350.version>3.5.0</spark350.version>

scala2.13/pom.xml

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<!-- Note Databricks requires 2 properties -Ddatabricks and -Dbuildver=3*db -->
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<!-- #if scala-2.12 --><!--
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<profile>
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<id>release332db</id>
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<activation>
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<property>
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<name>buildver</name>
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<value>332db</value>
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</property>
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</activation>
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<properties>
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<spark.version.classifier>spark332db</spark.version.classifier>
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<spark.version>${spark332db.version}</spark.version>
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<spark.test.version>${spark332db.version}</spark.test.version>
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<hadoop.client.version>3.3.1</hadoop.client.version>
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<rat.consoleOutput>true</rat.consoleOutput>
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<parquet.hadoop.version>1.12.0</parquet.hadoop.version>
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<rapids.delta.artifactId1>rapids-4-spark-delta-${spark.version.classifier}</rapids.delta.artifactId1>
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</properties>
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<modules>
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<module>shim-deps/databricks</module>
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<module>delta-lake/delta-spark332db</module>
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<module>iceberg/iceberg-stub</module>
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</modules>
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</profile>
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<profile>
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<id>release341db</id>
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<activation>
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<spark342.version>3.4.2</spark342.version>
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<spark343.version>3.4.3</spark343.version>
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<spark344.version>3.4.4</spark344.version>
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<spark332db.version>3.3.2-databricks</spark332db.version>
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<spark341db.version>3.4.1-databricks</spark341db.version>
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<spark350db143.version>3.5.0-databricks-143</spark350db143.version>
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<spark350.version>3.5.0</spark350.version>

scala2.13/shim-deps/pom.xml

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</dependency>
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</dependencies>
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</profile>
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<profile>
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<id>release332db</id>
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<activation>
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<property>
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<name>buildver</name>
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<value>332db</value>
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</property>
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</activation>
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<dependencies>
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<dependency>
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<groupId>org.apache.logging.log4j</groupId>
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<artifactId>log4j-core</artifactId>
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<version>${spark.version}</version>
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<scope>provided</scope>
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</dependency>
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</dependencies>
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</profile>
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<profile>
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<id>release341db</id>
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<activation>

shim-deps/pom.xml

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</dependency>
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</dependencies>
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</profile>
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<profile>
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<id>release332db</id>
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<activation>
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<property>
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<name>buildver</name>
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<value>332db</value>
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</property>
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</activation>
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<dependencies>
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<dependency>
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<groupId>org.apache.logging.log4j</groupId>
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<artifactId>log4j-core</artifactId>
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<version>${spark.version}</version>
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<scope>provided</scope>
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</dependency>
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</dependencies>
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</profile>
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<profile>
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<id>release341db</id>
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<activation>

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