jerryshao commented on code in PR #9623: URL: https://github.com/apache/gravitino/pull/9623#discussion_r2697876602
########## docs/lance-rest-integration.md: ########## @@ -0,0 +1,245 @@ +--- +title: "Lance REST Integration with Spark and Ray" +slug: /lance-rest-integration +keywords: + - lance + - lance-rest + - spark + - ray + - integration +license: "This software is licensed under the Apache License version 2." +--- + +## Overview + +This guide provides comprehensive instructions for integrating the Apache Gravitino Lance REST service with data processing engines that support the Lance format, including Apache Spark via the [Lance Spark connector](https://lance.org/integrations/spark/) and Ray via the [Lance Ray connector](https://lance.org/integrations/ray/). + +This documentation assumes familiarity with the Lance REST service setup as described in the [Lance REST Service](./lance-rest-service) documentation. + +## Compatibility Matrix + +The following table outlines the tested compatibility between Gravitino versions and Lance connector versions: + +| Gravitino Version (Lance REST) | Supported lance-spark Versions | Supported lance-ray Versions | +|--------------------------------|--------------------------------|------------------------------| +| 1.1.1 | 0.0.10 – 0.0.15 | 0.0.6 – 0.0.8 | + +:::note +- These version ranges represent combinations expected to be compatible based on API stability and feature sets. +- While broad compatibility is anticipated within these ranges, only select versions have been explicitly tested. +- We strongly recommend validating specific connector versions in your development environment before production deployment. +- As the Lance ecosystem evolves rapidly, API changes may introduce breaking changes between versions. +::: + +### Why Maintain a Compatibility Matrix? + +The Lance ecosystem is under active development, with frequent updates to APIs and features. Gravitino's Lance REST service depends on specific connector behaviors to ensure reliable operation. Using incompatible versions may result in: + +- Runtime errors or exceptions +- Data corruption or loss +- Unexpected behavior in query execution +- Performance degradation + +## Prerequisites + +Before proceeding, ensure the following requirements are met: + +1. **Gravitino Server**: A running Gravitino server instance with the Lance REST service enabled + - Default endpoint: `http://localhost:9101/lance` + +2. **Lance Catalog**: A Lance catalog created in Gravitino using either: + - Lance REST namespace API (`CreateNamespace` operation - see [Lance REST Service documentation](./lance-rest-service.md) + - Gravitino REST API, for more, please refer to [lakehouse-generic-catalog](./lakehouse-generic-catalog.md) + - Example catalog name: `lance_catalog` + +3. **Lance Spark Bundle** (for Spark integration): + - Downloaded `lance-spark` bundle JAR matching your Apache Spark version + - Note the absolute file path for configuration + +4. **Python Dependencies**: + - For Spark integration: `pyspark` + - For Ray integration: `ray`, `lance-namespace`, `lance-ray` + +## Spark Integration + +### Configuration + +The following example demonstrates how to configure a PySpark session to interact with Lance REST and perform table operations using Spark SQL. + +```python +from pyspark.sql import SparkSession +import os +import logging + +# Configure logging for debugging +logging. basicConfig(level=logging.INFO) + +# Configure Spark to use the lance-spark bundle +# Replace /path/to/lance-spark-bundle-3.5_2.12-0.0.15.jar with your actual JAR path +os.environ["PYSPARK_SUBMIT_ARGS"] = ( + "--jars /path/to/lance-spark-bundle-3.5_2.12-0.0.15.jar " + "--conf \"spark.driver.extraJavaOptions=--add-opens=java.base/sun.nio.ch=ALL-UNNAMED\" " + "--conf \"spark.executor.extraJavaOptions=--add-opens=java. base/sun.nio.ch=ALL-UNNAMED\" " + "--master local[1] pyspark-shell" +) + +# Initialize Spark session with Lance REST catalog configuration +# Note: The catalog "lance_catalog" must exist in Gravitino before running this code, you can create +# it via Lance REST API `CreateNameSpace` or Gravitino REST API `CreateCatalog`. +spark = SparkSession.builder \ + .appName("lance_rest_integration") \ + .config("spark.sql.catalog.lance", "com.lancedb.lance. spark.LanceNamespaceSparkCatalog") \ + .config("spark.sql.catalog.lance.impl", "rest") \ + .config("spark. sql.catalog.lance.uri", "http://localhost:9101/lance";) \ + .config("spark.sql.catalog.lance. parent", "lance_catalog") \ + .config("spark.sql.defaultCatalog", "lance") \ + .getOrCreate() + +# Enable debug logging for troubleshooting +spark.sparkContext.setLogLevel("DEBUG") + +# Create schema (database) +spark.sql("CREATE DATABASE IF NOT EXISTS sales") + +# Create Lance table with explicit location +spark.sql(""" + CREATE TABLE sales.orders ( + id INT, + score FLOAT + ) + USING lance + LOCATION '/tmp/sales/orders.lance/' + TBLPROPERTIES ('format' = 'lance') +""") + +# Insert sample data +spark.sql("INSERT INTO sales.orders VALUES (1, 1.1)") + +# Query data +spark.sql("SELECT * FROM sales.orders").show() +``` + +### Storage Location Configuration + +#### Local Storage + +The `LOCATION` clause in the `CREATE TABLE` statement is optional. When omitted, lance-spark automatically determines an appropriate storage location based on catalog properties. +For detailed information on location resolution logic, refer to the [Lakehouse Generic Catalog documentation](./lakehouse-generic-catalog.md#key-property-location). + +#### Cloud Storage (S3-Compatible) + +For cloud storage backends such as Amazon S3 or MinIO, specify credentials and endpoint configuration in the table properties: + +```python +spark.sql(""" + CREATE TABLE sales.orders ( + id INT, + score FLOAT + ) + USING lance + LOCATION 's3://bucket/tmp/sales/orders.lance/' + TBLPROPERTIES ( + 'format' = 'lance', + 'lance.storage.access_key_id' = 'your_access_key', + 'lance.storage.secret_access_key' = 'your_secret_key', + 'lance.storage.endpoint' = 'http://minio:9000', + 'lance.storage.allow_http' = 'true' + ) +""") +``` + +:::warning +Never hardcode credentials in production code. Use environment variables, secret management systems, or IAM roles for credential management. +::: + +## Ray Integration + +### Installation + +Install the required Ray integration packages: + +```shell +pip install lance-ray +``` + +:::info +- Ray will be automatically installed if not already present +- lance-ray is currently tested with Ray versions 2.41.0 to 2.50.0 +- Ensure Ray version compatibility in your environment before deployment +::: + +### Usage Example + +The following example demonstrates reading and writing Lance datasets through the Lance REST namespace using Ray: + +```python +import ray +import lance_namespace as ln +from lance_ray import read_lance, write_lance + +# Initialize Ray runtime +ray.init() + +# Connect to Lance REST namespace +namespace = ln.connect("rest", {"uri": "http://localhost:9101/lance"}) + +# Create sample dataset +data = ray.data.range(1000).map( + lambda row: {"id": row["id"], "value": row["id"] * 2} +) + +# Write dataset to Lance table +# Note: Both the catalog "lance_catalog" and schema "sales" must exist in Gravitino, you can create +# them via Lance REST API `CreateNameSpace` or Gravitino REST API `CreateCatalog` and `CreateSchema`. +write_lance( + data, + namespace=namespace, + table_id=["lance_catalog", "sales", "orders"] +) + +# Read dataset from Lance table +ray_dataset = read_lance( + namespace=namespace, + table_id=["lance_catalog", "sales", "orders"] +) + +# Perform filtering operation +result = ray_dataset.filter(lambda row: row["value"] < 100).count() +print(f"Filtered row count: {result}") +``` + +### Important Considerations + +- **Namespace Hierarchy**: The `table_id` parameter uses a hierarchical structure: `["catalog_name", "sales", "orders"]` +- **Pre-requisites**: Both the target catalog (`lance_catalog`) and schema (`sales`) must be created in Gravitino before executing write operations +- **Error Handling**: Implement appropriate error handling for network failures and authentication issues in production environments Review Comment: Is it necessary to mention here? -- This is an automated message from the Apache Git Service. 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