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Posted to commits@spark.apache.org by gu...@apache.org on 2018/12/21 08:10:32 UTC
[spark] branch branch-2.4 updated: [SPARK-26422][R] Support to
disable Hive support in SparkR even for Hadoop versions unsupported by Hive
fork
This is an automated email from the ASF dual-hosted git repository.
gurwls223 pushed a commit to branch branch-2.4
in repository https://gitbox.apache.org/repos/asf/spark.git
The following commit(s) were added to refs/heads/branch-2.4 by this push:
new 90a14d5 [SPARK-26422][R] Support to disable Hive support in SparkR even for Hadoop versions unsupported by Hive fork
90a14d5 is described below
commit 90a14d58b4e87a603e35a9ab679f6049b10e9c7b
Author: Hyukjin Kwon <gu...@apache.org>
AuthorDate: Fri Dec 21 16:09:30 2018 +0800
[SPARK-26422][R] Support to disable Hive support in SparkR even for Hadoop versions unsupported by Hive fork
## What changes were proposed in this pull request?
Currently, even if I explicitly disable Hive support in SparkR session as below:
```r
sparkSession <- sparkR.session("local[4]", "SparkR", Sys.getenv("SPARK_HOME"),
enableHiveSupport = FALSE)
```
produces when the Hadoop version is not supported by our Hive fork:
```
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)
```
The root cause is that:
```
SparkSession.hiveClassesArePresent
```
check if the class is loadable or not to check if that's in classpath but `org.apache.hadoop.hive.conf.HiveConf` has a check for Hadoop version as static logic which is executed right away. This throws an `IllegalArgumentException` and that's not caught:
https://github.com/apache/spark/blob/36edbac1c8337a4719f90e4abd58d38738b2e1fb/sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala#L1113-L1121
So, currently, if users have a Hive built-in Spark with unsupported Hadoop version by our fork (namely 3+), there's no way to use SparkR even though it could work.
This PR just propose to change the order of bool comparison so that we can don't execute `SparkSession.hiveClassesArePresent` when:
1. `enableHiveSupport` is explicitly disabled
2. `spark.sql.catalogImplementation` is `in-memory`
so that we **only** check `SparkSession.hiveClassesArePresent` when Hive support is explicitly enabled by short circuiting.
## How was this patch tested?
It's difficult to write a test since we don't run tests against Hadoop 3 yet. See https://github.com/apache/spark/pull/21588. Manually tested.
Closes #23356 from HyukjinKwon/SPARK-26422.
Authored-by: Hyukjin Kwon <gu...@apache.org>
Signed-off-by: Hyukjin Kwon <gu...@apache.org>
(cherry picked from commit 305e9b5ad22b428501fd42d3730d73d2e09ad4c5)
Signed-off-by: Hyukjin Kwon <gu...@apache.org>
---
.../src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala | 12 ++++++++++--
1 file changed, 10 insertions(+), 2 deletions(-)
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 af20764..4c71795 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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