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gcs-connector-3.0.0-shaded CVEs #1114

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wendigo opened this issue Feb 14, 2024 · 1 comment
Open

gcs-connector-3.0.0-shaded CVEs #1114

wendigo opened this issue Feb 14, 2024 · 1 comment

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@wendigo
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wendigo commented Feb 14, 2024

gcs-connector-3.0.0-shaded contains following CVEs:

Can you please upgrade guava dependency and release new version 3.0.x ?

@dongjoon-hyun
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+1 for this issue.

dongjoon-hyun added a commit to apache/spark that referenced this issue Apr 2, 2024
… for 3.0.0

### What changes were proposed in this pull request?

This PR aims to upgrade `gcs-connector` to 2.2.21 and add a note for 3.0.0.

### Why are the changes needed?

This PR aims to upgrade `gcs-connector` to bring the latest bug fixes.

However, due to the following, we stick to use 2.2.21.
- GoogleCloudDataproc/hadoop-connectors#1114
  - `gcs-connector` 2.2.21 has shaded Guava 32.1.2-jre.
    - https://github.com/GoogleCloudDataproc/hadoop-connectors/blob/15c8ee41a15d6735442f36333f1d67792c93b9cf/pom.xml#L100

  - `gcs-connector` 3.0.0 has shaded Guava 31.1-jre.
    - https://github.com/GoogleCloudDataproc/hadoop-connectors/blob/667bf17291dbaa96a60f06df58c7a528bc4a8f79/pom.xml#L97

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Manually.
```
$ 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"
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 4.0.0-SNAPSHOT
      /_/

Using Scala version 2.13.13 (OpenJDK 64-Bit Server VM, Java 21.0.2)
Type in expressions to have them evaluated.
Type :help for more information.
{"ts":"2024-04-02T13:08:31.513-0700","level":"WARN","msg":"Unable to load native-hadoop library for your platform... using builtin-java classes where applicable","logger":"org.apache.hadoop.util.NativeCodeLoader"}
Spark context Web UI available at http://localhost:4040
Spark context available as 'sc' (master = local[*], app id = local-1712088511841).
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.

Closes #45824 from dongjoon-hyun/SPARK-47699.

Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
szehon-ho pushed a commit to szehon-ho/spark that referenced this issue Aug 7, 2024
… for 3.0.0

This PR aims to upgrade `gcs-connector` to 2.2.21 and add a note for 3.0.0.

This PR aims to upgrade `gcs-connector` to bring the latest bug fixes.

However, due to the following, we stick to use 2.2.21.
- GoogleCloudDataproc/hadoop-connectors#1114
  - `gcs-connector` 2.2.21 has shaded Guava 32.1.2-jre.
    - https://github.com/GoogleCloudDataproc/hadoop-connectors/blob/15c8ee41a15d6735442f36333f1d67792c93b9cf/pom.xml#L100

  - `gcs-connector` 3.0.0 has shaded Guava 31.1-jre.
    - https://github.com/GoogleCloudDataproc/hadoop-connectors/blob/667bf17291dbaa96a60f06df58c7a528bc4a8f79/pom.xml#L97

No.

Manually.
```
$ 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"
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 4.0.0-SNAPSHOT
      /_/

Using Scala version 2.13.13 (OpenJDK 64-Bit Server VM, Java 21.0.2)
Type in expressions to have them evaluated.
Type :help for more information.
{"ts":"2024-04-02T13:08:31.513-0700","level":"WARN","msg":"Unable to load native-hadoop library for your platform... using builtin-java classes where applicable","logger":"org.apache.hadoop.util.NativeCodeLoader"}
Spark context Web UI available at http://localhost:4040
Spark context available as 'sc' (master = local[*], app id = local-1712088511841).
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|              []|
+------+--------------+----------------+
```

No.

Closes apache#45824 from dongjoon-hyun/SPARK-47699.

Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
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