[#4895] docs(iceberg): add document for support not managed storages for Iceberg #4896
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FANNG1
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jerryshao
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Sep 10, 2024
docs/iceberg-rest-service.md
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| |----------------------------------|-----------------------------------------------------------------------------------------|---------------|----------|---------------| | ||
| | `gravitino.iceberg-rest.io-impl` | The IO implementation for `FileIO` in Iceberg, please use the full qualified classname. | (none) | No | 0.6.0 | | ||
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| For other custom properties like `security-token` to pass to `FileIO`, you could config it directly by `gravitino.iceberg-rest.security-token`. |
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Can you explain more here? For example, if user has a custom FileIO implementation called "A", then set configuration like "gravitino.iceberg-rest.xxx", how does this "A" know this configuration "xxx"?
jerryshao
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Sep 10, 2024
docs/iceberg-rest-service.md
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| @@ -321,7 +332,7 @@ For example, we can configure Spark catalog options to use Gravitino Iceberg RES | |||
| --conf spark.sql.catalog.rest.uri=http://127.0.0.1:9001/iceberg/ | |||
| ``` | |||
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| You may need to adjust the Iceberg Spark runtime jar file name according to the real version number in your environment. If you want to access the data stored in S3, you need to download [Iceberg AWS bundle](https://mvnrepository.com/artifact/org.apache.iceberg/iceberg-aws-bundle) jar and place it in the classpath of Spark, no extra config is needed because S3 related properties is transferred from Iceberg REST server to Iceberg REST client automaticly. | |||
| You may need to adjust the Iceberg Spark runtime jar file name according to the real version number in your environment. If you want to access the data stored in S3, you need to download [Iceberg AWS bundle](https://mvnrepository.com/artifact/org.apache.iceberg/iceberg-aws-bundle) jar and place it in the classpath of Spark, no extra config is needed because S3 related properties is transferred from Iceberg REST server to Iceberg REST client automaticly. For other storages not managed by Gravitino, you could specify the configuration explicitly to initialize the `FileIO` implementation, like `spark.sql.catalog.${catalog_name}.${configuration_key}`. | |||
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Is it only for S3, how about other storages supported by Gravitino, and others not directly support by us?
Can you please describe more, and write them down as a user? I don't think users can handle this with such simple words, at least for me.
jerryshao
reviewed
Sep 10, 2024
docs/lakehouse-iceberg-catalog.md
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| #### Other storages | ||
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| For storages that are not inherently integrated into Gravitino Iceberg REST service, you can manage them effectively through custom catalog properties. |
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What's the meaning of "inherently integrated"?
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jerryshao
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Sep 11, 2024
docs/iceberg-rest-service.md
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| - HDFS | ||
| - S3 | ||
| - OSS | ||
| - Supports diverse storage like `S3`, `HDFS`, `OSS`, and provides the capability to support other storages. |
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I believe there's gcs, right? Please list all the supported cloud storage.
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"Supports different cloud storages...: "
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using Supports different storages, because HDFS is not cloud storage
jerryshao
reviewed
Sep 11, 2024
docs/iceberg-rest-service.md
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| @@ -337,7 +348,7 @@ For example, we can configure Spark catalog options to use Gravitino Iceberg RES | |||
| --conf spark.sql.catalog.rest.uri=http://127.0.0.1:9001/iceberg/ | |||
| ``` | |||
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| You may need to adjust the Iceberg Spark runtime jar file name according to the real version number in your environment. If you want to access the data stored in cloud, you need to download corresponding jars (please refer to the cloud storage part) and place it in the classpath of Spark, no extra config is needed because related properties is transferred from Iceberg REST server to Iceberg REST client automatically. | |||
| You may need to adjust the Iceberg Spark runtime jar file name according to the real version number in your environment. If you want to access the data stored in cloud, you need to download corresponding jars (please refer to the cloud storage part) and place it in the classpath of Spark, no extra config is needed because related properties is transferred from Iceberg REST server to Iceberg REST client automatically. For other storages not managed by Gravitino, the properties wouldn't transfer from the server to client automatically, if you want to pass custom properties to initialize `FileIO`, you could add it by `spark.sql.catalog.${iceberg_catalog_name}.${configuration_key}` = `{property_value}`. | |||
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Can you please split this long sentence into several paragraphs to make it more clear.
jerryshao
reviewed
Sep 11, 2024
docs/lakehouse-iceberg-catalog.md
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| @@ -119,6 +119,20 @@ Please make sure the credential file is accessible by Gravitino, like using `exp | |||
| Please set `warehouse` to `gs://{bucket_name}/${prefix_name}`, and download [Iceberg gcp bundle jar](https://mvnrepository.com/artifact/org.apache.iceberg/iceberg-gcp-bundle) and place it to `catalogs/lakehouse-iceberg/libs/`. | |||
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| #### Other storages | |||
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| For other storages that are managed by Gravitino directly, you can manage them through custom catalog properties. | |||
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“that are not managed...”
jerryshao
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Sep 11, 2024
docs/iceberg-rest-service.md
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| @@ -162,6 +159,20 @@ You should place HDFS configuration file to the classpath of the Iceberg REST se | |||
| Builds with Hadoop 2.10.x. There may be compatibility issues when accessing Hadoop 3.x clusters. | |||
| ::: | |||
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| #### Other storages | |||
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| For other storages that are managed by Gravitino directly, you can manage them through custom catalog properties. | |||
jerryshao
approved these changes
Sep 12, 2024
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What changes were proposed in this pull request?
For other storage not build in with Gravitino, we should add a document about how to run it
Why are the changes needed?
Fix: #4895
Does this PR introduce any user-facing change?
no
How was this patch tested?
existing tests