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https://issues.apache.org/jira/browse/SPARK-26422?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16726526#comment-16726526
]
ASF GitHub Bot commented on SPARK-26422:
----------------------------------------
asfgit closed pull request #23356: [SPARK-26422][R] Support to disable Hive
support in SparkR even for Hadoop versions unsupported by Hive fork
URL: https://github.com/apache/spark/pull/23356
This is a PR merged from a forked repository.
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diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
index becb05cf72aba..e98cab8b56d13 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
@@ -49,9 +49,17 @@ private[sql] object SQLUtils extends Logging {
sparkConfigMap: JMap[Object, Object],
enableHiveSupport: Boolean): SparkSession = {
val spark =
- if (SparkSession.hiveClassesArePresent && enableHiveSupport &&
+ if (enableHiveSupport &&
jsc.sc.conf.get(CATALOG_IMPLEMENTATION.key,
"hive").toLowerCase(Locale.ROOT) ==
- "hive") {
+ "hive" &&
+ // Note that the order of conditions here are on purpose.
+ // `SparkSession.hiveClassesArePresent` checks if Hive's `HiveConf`
is loadable or not;
+ // however, `HiveConf` itself has some static logic to check if
Hadoop version is
+ // supported or not, which throws an `IllegalArgumentException` if
unsupported.
+ // If this is checked first, there's no way to disable Hive support
in the case above.
+ // So, we intentionally check if Hive classes are loadable or not
only when
+ // Hive support is explicitly enabled by short-circuiting. See also
SPARK-26422.
+ SparkSession.hiveClassesArePresent) {
SparkSession.builder().sparkContext(withHiveExternalCatalog(jsc.sc)).getOrCreate()
} else {
if (enableHiveSupport) {
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> Unable to disable Hive support in SparkR when Hadoop version is unsupported
> ---------------------------------------------------------------------------
>
> Key: SPARK-26422
> URL: https://issues.apache.org/jira/browse/SPARK-26422
> Project: Spark
> Issue Type: Bug
> Components: SparkR
> Affects Versions: 3.0.0
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Priority: Major
> Fix For: 2.3.3, 2.4.1, 3.0.0
>
>
> When we make a Spark session as below:
> {code}
> sparkSession <- sparkR.session("local[4]", "SparkR", Sys.getenv("SPARK_HOME"),
> list(spark.driver.extraClassPath = jarpaths,
> spark.executor.extraClassPath = jarpaths),
> enableHiveSupport = FALSE)
> {code}
> I faced an issue that it's unable to disable Hive support explicitly with the
> error below:
> {code}
> java.lang.reflect.InvocationTargetException
> ...
> Caused by: java.lang.IllegalArgumentException: Unrecognized Hadoop major
> version number: 3.1.1.3.1.0.0-78
> at
> org.apache.hadoop.hive.shims.ShimLoader.getMajorVersion(ShimLoader.java:174)
> at
> org.apache.hadoop.hive.shims.ShimLoader.loadShims(ShimLoader.java:139)
> at
> org.apache.hadoop.hive.shims.ShimLoader.getHadoopShims(ShimLoader.java:100)
> at
> org.apache.hadoop.hive.conf.HiveConf$ConfVars.<clinit>(HiveConf.java:368)
> ... 43 more
> Error in handleErrors(returnStatus, conn) :
> java.lang.ExceptionInInitializerError
> at org.apache.hadoop.hive.conf.HiveConf.<clinit>(HiveConf.java:105)
> at java.lang.Class.forName0(Native Method)
> at java.lang.Class.forName(Class.java:348)
> at org.apache.spark.util.Utils$.classForName(Utils.scala:193)
> at
> org.apache.spark.sql.SparkSession$.hiveClassesArePresent(SparkSession.scala:1116)
> at
> org.apache.spark.sql.api.r.SQLUtils$.getOrCreateSparkSession(SQLUtils.scala:52)
> at
> org.apache.spark.sql.api.r.SQLUtils.getOrCreateSparkSession(SQLUtils.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.apache.spark.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:167)
> at
> org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:108)
> ...
> {code}
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