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Using S3 with Gluten |
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Getting-Started |
Object stores offered by CSPs such as AWS S3 are important for users of Gluten to store their data. This doc will discuss all details of configs, and use cases around using Gluten with object stores. In order to use an S3 endpoint as your data source, please ensure you are using the following S3 configs in your spark-defaults.conf. If you're experiencing any issues authenticating to S3 with additional auth mechanisms, please reach out to us using the 'Issues' tab.
S3 provides the endpoint based method to access the files, here's the example configuration. Users may need to modify some values based on real setup.
spark.hadoop.fs.s3a.impl org.apache.hadoop.fs.s3a.S3AFileSystem
spark.hadoop.fs.s3a.aws.credentials.provider org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider
spark.hadoop.fs.s3a.access.key XXXXXXXXX
spark.hadoop.fs.s3a.secret.key XXXXXXXXX
spark.hadoop.fs.s3a.endpoint https://s3.us-west-1.amazonaws.com
spark.hadoop.fs.s3a.connection.ssl.enabled true
spark.hadoop.fs.s3a.path.style.access false
S3 also provides other methods for accessing, you can also use instance credentials by setting the following config
spark.hadoop.fs.s3a.use.instance.credentials true
Note that in this case, "spark.hadoop.fs.s3a.endpoint" won't take affect as Gluten will use the endpoint set during instance creation.
You can also use iam role credentials by setting the following configurations. Instance credentials have higher priority than iam credentials.
spark.hadoop.fs.s3a.iam.role xxxx
spark.hadoop.fs.s3a.iam.role.session.name xxxx
Note that spark.hadoop.fs.s3a.iam.role.session.name
is optional.
You can change log granularity of AWS C++ SDK by setting the spark.gluten.velox.awsSdkLogLevel
configuration. The Allowed values are:
- OFF
- FATAL
- ERROR
- WARN
- INFO
- DEBUG
- TRACE
Velox supports a local cache when reading data from S3. Please refer Velox Local Cache part for more detailed configurations.