yuqi1129 commented on code in PR #6059:
URL: https://github.com/apache/gravitino/pull/6059#discussion_r1908941054
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docs/hadoop-catalog-with-adls.md:
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+---
+title: "Hadoop catalog with ADLS"
+slug: /hadoop-catalog-with-adls
+date: 2025-01-03
+keyword: Hadoop catalog ADLS
+license: "This software is licensed under the Apache License version 2."
+---
+
+This document describes how to configure a Hadoop catalog with ADLS (Azure
Blob Storage).
+
+## Prerequisites
+
+To set up a Hadoop catalog with ADLS, follow these steps:
+
+1. Download the
[`gravitino-azure-bundle-${gravitino-version}.jar`](https://mvnrepository.com/artifact/org.apache.gravitino/gravitino-azure-bundle)
file.
+2. Place the downloaded file into the Gravitino Hadoop catalog classpath at
`${GRAVITINO_HOME}/catalogs/hadoop/libs/`.
+3. Start the Gravitino server by running the following command:
+
+```bash
+$ bin/gravitino-server.sh start
+```
+Once the server is up and running, you can proceed to configure the Hadoop
catalog with ADLS.
+
+## Configurations for creating a Hadoop catalog with ADLS
+
+### Configuration for a ADLS Hadoop catalog
+
+Apart from configurations mentioned in
[Hadoop-catalog-catalog-configuration](./hadoop-catalog.md#catalog-properties),
the following properties are required to configure a Hadoop catalog with ADLS:
+
+| Configuration item | Description
| Default value | Required | Since
version |
+|-----------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------|----------|------------------|
+| `filesystem-providers` | The file system providers to add. Set it
to `abs` if it's a Azure Blob Storage fileset, or a comma separated string that
contains `abs` like `oss,abs,s3` to support multiple kinds of fileset including
`abs`. | (none) | Yes |
0.8.0-incubating |
+| `default-filesystem-provider` | The name default filesystem providers of
this Hadoop catalog if users do not specify the scheme in the URI. Default
value is `builtin-local`, for Azure Blob Storage, if we set this value, we can
omit the prefix 'abfss://' in the location. | `builtin-local` | No |
0.8.0-incubating |
+| `azure-storage-account-name ` | The account name of Azure Blob Storage.
| (none) | Yes |
0.8.0-incubating |
+| `azure-storage-account-key` | The account key of Azure Blob Storage.
| (none) | Yes |
0.8.0-incubating |
+
+### Configurations for a schema
+
+Refer to [Schema configurations](./hadoop-catalog.md#schema-properties) for
more details.
+
+### Configurations for a fileset
+
+Refer to [Fileset configurations](./hadoop-catalog.md#fileset-properties) for
more details.
+
+## Example of creating Hadoop catalog with ADLS
+
+This section demonstrates how to create the Hadoop catalog with ADLS in
Gravitino, with a complete example.
+
+### Step1: Create a Hadoop catalog with ADLS
+
+First, you need to create a Hadoop catalog with ADLS. The following example
shows how to create a Hadoop catalog with ADLS:
+
+<Tabs groupId="language" queryString>
+<TabItem value="shell" label="Shell">
+
+```shell
+curl -X POST -H "Accept: application/vnd.gravitino.v1+json" \
+-H "Content-Type: application/json" -d '{
+ "name": "example_catalog",
+ "type": "FILESET",
+ "comment": "This is a ADLS fileset catalog",
+ "provider": "hadoop",
+ "properties": {
+ "location": "abfss://contai...@account-name.dfs.core.windows.net/path",
+ "azure-storage-account-name": "The account name of the Azure Blob Storage",
+ "azure-storage-account-key": "The account key of the Azure Blob Storage",
+ "filesystem-providers": "abs"
+ }
+}' ${GRAVITINO_SERVER_IP:PORT}/api/metalakes/metalake/catalogs
+```
+
+</TabItem>
+<TabItem value="java" label="Java">
+
+```java
+GravitinoClient gravitinoClient = GravitinoClient
+ .builder("${GRAVITINO_SERVER_IP:PORT}")
+ .withMetalake("metalake")
+ .build();
+
+adlsProperties = ImmutableMap.<String, String>builder()
+ .put("location",
"abfss://contai...@account-name.dfs.core.windows.net/path")
+ .put("azure-storage-account-name", "azure storage account name")
+ .put("azure-storage-account-key", "azure storage account key")
+ .put("filesystem-providers", "abs")
+ .build();
+
+Catalog adlsCatalog = gravitinoClient.createCatalog("example_catalog",
+ Type.FILESET,
+ "hadoop", // provider, Gravitino only supports "hadoop" for now.
+ "This is a ADLS fileset catalog",
+ adlsProperties);
+// ...
+
+```
+
+</TabItem>
+<TabItem value="python" label="Python">
+
+```python
+gravitino_client: GravitinoClient =
GravitinoClient(uri="${GRAVITINO_SERVER_IP:PORT}", metalake_name="metalake")
+adls_properties = {
+ "location": "abfss://contai...@account-name.dfs.core.windows.net/path",
+ "azure-storage-account-name": "azure storage account name",
+ "azure-storage-account-key": "azure storage account key",
+ "filesystem-providers": "abs"
+}
+
+adls_properties = gravitino_client.create_catalog(name="example_catalog",
+ type=Catalog.Type.FILESET,
+ provider="hadoop",
+ comment="This is a ADLS fileset
catalog",
+ properties=adls_properties)
+
+```
+
+</TabItem>
+</Tabs>
+
+### Step2: Create a schema
+
+Once the catalog is created, you can create a schema. The following example
shows how to create a schema:
+
+<Tabs groupId="language" queryString>
+<TabItem value="shell" label="Shell">
+
+```shell
+curl -X POST -H "Accept: application/vnd.gravitino.v1+json" \
+-H "Content-Type: application/json" -d '{
+ "name": "test_schema",
+ "comment": "This is a ADLS schema",
+ "properties": {
+ "location": "abfss://contai...@account-name.dfs.core.windows.net/path"
+ }
+}'
${GRAVITINO_SERVER_IP:PORT}/api/metalakes/metalake/catalogs/test_catalog/schemas
+```
+
+</TabItem>
+<TabItem value="java" label="Java">
+
+```java
+Catalog catalog = gravitinoClient.loadCatalog("test_catalog");
+
+SupportsSchemas supportsSchemas = catalog.asSchemas();
+
+Map<String, String> schemaProperties = ImmutableMap.<String, String>builder()
+ .put("location",
"abfss://contai...@account-name.dfs.core.windows.net/path")
+ .build();
+Schema schema = supportsSchemas.createSchema("test_schema",
+ "This is a ADLS schema",
+ schemaProperties
+);
+// ...
+```
+
+</TabItem>
+<TabItem value="python" label="Python">
+
+```python
+gravitino_client: GravitinoClient =
GravitinoClient(uri="http://127.0.0.1:8090";, metalake_name="metalake")
+catalog: Catalog = gravitino_client.load_catalog(name="test_catalog")
+catalog.as_schemas().create_schema(name="test_schema",
+ comment="This is a ADLS schema",
+ properties={"location":
"abfss://contai...@account-name.dfs.core.windows.net/path"})
+```
+
+</TabItem>
+</Tabs>
+
+### Step3: Create a fileset
+
+After creating the schema, you can create a fileset. The following example
shows how to create a fileset:
+
+<Tabs groupId="language" queryString>
+<TabItem value="shell" label="Shell">
+
+```shell
+curl -X POST -H "Accept: application/vnd.gravitino.v1+json" \
+-H "Content-Type: application/json" -d '{
+ "name": "example_fileset",
+ "comment": "This is an example fileset",
+ "type": "MANAGED",
+ "storageLocation":
"abfss://contai...@account-name.dfs.core.windows.net/path/example_fileset",
+ "properties": {
+ "k1": "v1"
+ }
+}'
${GRAVITINO_SERVER_IP:PORT}/api/metalakes/metalake/catalogs/test_catalog/schemas/test_schema/filesets
+```
+
+</TabItem>
+<TabItem value="java" label="Java">
+
+```java
+GravitinoClient gravitinoClient = GravitinoClient
+ .builder("${GRAVITINO_SERVER_IP:PORT}")
+ .withMetalake("metalake")
+ .build();
+
+Catalog catalog = gravitinoClient.loadCatalog("test_catalog");
+FilesetCatalog filesetCatalog = catalog.asFilesetCatalog();
+
+Map<String, String> propertiesMap = ImmutableMap.<String, String>builder()
+ .put("k1", "v1")
+ .build();
+
+filesetCatalog.createFileset(
+ NameIdentifier.of("test_schema", "example_fileset"),
+ "This is an example fileset",
+ Fileset.Type.MANAGED,
+ "abfss://contai...@account-name.dfs.core.windows.net/path/example_fileset",
+ propertiesMap,
+);
+```
+
+</TabItem>
+<TabItem value="python" label="Python">
+
+```python
+gravitino_client: GravitinoClient =
GravitinoClient(uri="${GRAVITINO_SERVER_IP:PORT}", metalake_name="metalake")
+
+catalog: Catalog = gravitino_client.load_catalog(name="test_catalog")
+catalog.as_fileset_catalog().create_fileset(ident=NameIdentifier.of("test_schema",
"example_fileset"),
+ type=Fileset.Type.MANAGED,
+ comment="This is an example
fileset",
+
storage_location="abfss://contai...@account-name.dfs.core.windows.net/path/example_fileset",
+ properties={"k1": "v1"})
+```
+
+</TabItem>
+</Tabs>
+
+## Accessing a fileset with ADLS
+
+### Using Spark to access the fileset
+
+The following code snippet shows how to use **PySpark 3.1.3 with Hadoop
environment(Hadoop 3.2.0)** to access the fileset:
+
+```python
+import logging
+from gravitino import NameIdentifier, GravitinoClient, Catalog, Fileset,
GravitinoAdminClient
+from pyspark.sql import SparkSession
+import os
+
+gravitino_url = "${GRAVITINO_SERVER_IP:PORT}"
+metalake_name = "test"
+
+catalog_name = "your_adls_catalog"
+schema_name = "your_adls_schema"
+fileset_name = "your_adls_fileset"
+
+os.environ["PYSPARK_SUBMIT_ARGS"] = "--jars
/path/to/gravitino-azure-{gravitino-version}.jar,/path/to/gravitino-filesystem-hadoop3-runtime-{gravitino-version}.jar,/path/to/hadoop-azure-3.2.0.jar,/path/to/azure-storage-7.0.0.jar,/path/to/wildfly-openssl-1.0.4.Final.jar
--master local[1] pyspark-shell"
+spark = SparkSession.builder
+.appName("adls_fileset_test")
+.config("spark.hadoop.fs.AbstractFileSystem.gvfs.impl",
"org.apache.gravitino.filesystem.hadoop.Gvfs")
+.config("spark.hadoop.fs.gvfs.impl",
"org.apache.gravitino.filesystem.hadoop.GravitinoVirtualFileSystem")
+.config("spark.hadoop.fs.gravitino.server.uri", "${GRAVITINO_SERVER_URL}")
+.config("spark.hadoop.fs.gravitino.client.metalake", "test")
+.config("spark.hadoop.azure-storage-account-name", "azure_account_name")
+.config("spark.hadoop.azure-storage-account-key", "azure_account_name")
+.config("spark.hadoop.fs.azure.skipUserGroupMetadataDuringInitialization",
"true")
+.config("spark.driver.memory", "2g")
+.config("spark.driver.port", "2048")
+.getOrCreate()
+
+data = [("Alice", 25), ("Bob", 30), ("Cathy", 45)]
+columns = ["Name", "Age"]
+spark_df = spark.createDataFrame(data, schema=columns)
+gvfs_path =
f"gvfs://fileset/{catalog_name}/{schema_name}/{fileset_name}/people"
+
+spark_df.coalesce(1).write
+.mode("overwrite")
+.option("header", "true")
+.csv(gvfs_path)
+```
+
+If your Spark **without Hadoop environment**, you can use the following code
snippet to access the fileset:
+
+```python
+## Replace the following code snippet with the above code snippet with the
same environment variables
+
+os.environ["PYSPARK_SUBMIT_ARGS"] = "--jars
/path/to/gravitino-azure-bundle-{gravitino-version}.jar,/path/to/gravitino-filesystem-hadoop3-runtime-{gravitino-version}.jar
--master local[1] pyspark-shell"
+```
+
+-
[`gravitino-azure-bundle-${gravitino-version}.jar`](https://mvnrepository.com/artifact/org.apache.gravitino/gravitino-azure-bundle)
is the Gravitino ADLS jar with Hadoop environment and `hadoop-azure` jar.
+-
[`gravitino-azure-${gravitino-version}.jar`](https://mvnrepository.com/artifact/org.apache.gravitino/gravitino-azure)
is a condensed version of the Gravitino ADLS bundle jar without Hadoop
environment and `hadoop-azure` jar.
+- `hadoop-azure-3.2.0.jar` and `azure-storage-7.0.0.jar` can be found in the
Hadoop distribution in the `${HADOOP_HOME}/share/hadoop/tools/lib` directory.
+
+
+Please choose the correct jar according to your environment.
+
+:::note
+In some Spark versions, a Hadoop environment is needed by the driver, adding
the bundle jars with '--jars' may not work. If this is the case, you should add
the jars to the spark CLASSPATH directly.
+:::
+
+### Using Gravitino virtual file system Java client to access the fileset
Review Comment:
Maybe we could use `Using JAVA GVFS client to access the fileset`
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