dongjoon-hyun opened a new pull request, #53690:
URL: https://github.com/apache/spark/pull/53690

   ### What changes were proposed in this pull request?
   
   This PR aims to upgrade `gcs-connector` to 2.2.31 for Apache Spark 4.2.0.
   
   ### Why are the changes needed?
   
   To bring the latest bug fixes.
   - 
https://github.com/GoogleCloudDataproc/hadoop-connectors/releases/tag/v2.2.31
   - 
https://github.com/GoogleCloudDataproc/hadoop-connectors/releases/tag/v2.2.30
   
   ### Does this PR introduce _any_ user-facing change?
   
   No behavior change.
   
   ### How was this patch tested?
   
   ```
   $ dev/make-distribution.sh -Phadoop-cloud
   $ cd dist
   $ export KEYFILE=~/.ssh/apache-spark.json
   $ export EMAIL=$(jq -r '.client_email' < $KEYFILE)
   $ export PRIVATE_KEY_ID=$(jq -r '.private_key_id' < $KEYFILE)
   $ export PRIVATE_KEY="$(jq -r '.private_key' < $KEYFILE)"
   $ bin/spark-shell \
     -c spark.hadoop.fs.gs.auth.service.account.email=$EMAIL \
     -c spark.hadoop.fs.gs.auth.service.account.private.key.id=$PRIVATE_KEY_ID \
     -c spark.hadoop.fs.gs.auth.service.account.private.key="$PRIVATE_KEY"
   WARNING: Using incubator modules: jdk.incubator.vector
   Using Spark's default log4j profile: 
org/apache/spark/log4j2-defaults.properties
   Setting default log level to "WARN".
   To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use 
setLogLevel(newLevel).
   Welcome to
         ____              __
        / __/__  ___ _____/ /__
       _\ \/ _ \/ _ `/ __/  '_/
      /___/ .__/\_,_/_/ /_/\_\   version 4.2.0-SNAPSHOT
         /_/
   
   Using Scala version 2.13.18 (OpenJDK 64-Bit Server VM, Java 17.0.17)
   Type in expressions to have them evaluated.
   Type :help for more information.
   26/01/06 13:31:11 WARN NativeCodeLoader: Unable to load native-hadoop 
library for your platform... using builtin-java classes where applicable
   Spark context Web UI available at http://localhost:4040
   Spark context available as 'sc' (master = local[*], app id = 
local-1767673872877).
   Spark session available as 'spark'.
   
   scala> spark.read.text("gs://apache-spark-bucket/README.md").count()
   val res0: Long = 124
   
   scala> 
spark.read.orc("examples/src/main/resources/users.orc").write.mode("overwrite").orc("gs://apache-spark-bucket/users.orc")
   
   scala> spark.read.orc("gs://apache-spark-bucket/users.orc").show()
   +------+--------------+----------------+
   |  name|favorite_color|favorite_numbers|
   +------+--------------+----------------+
   |Alyssa|          NULL|  [3, 9, 15, 20]|
   |   Ben|           red|              []|
   +------+--------------+----------------+
   ```
   
   ### Was this patch authored or co-authored using generative AI tooling?
   
   No.


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