eric-maynard commented on code in PR #1503: URL: https://github.com/apache/polaris/pull/1503#discussion_r2069772410
########## site/content/in-dev/unreleased/polaris-spark-client.md: ########## @@ -0,0 +1,155 @@ +--- +# +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +# +Title: Polaris Spark Client +type: docs +weight: 400 +--- + +Apache Polaris now provides Catalog support for Generic Tables (non-iceberg tables), please check out +the [Catalog API Spec]({{% ref "polaris-catalog-service" %}}) for Generic Table API specs. + +Along with the Generic Table Catalog support, Polaris is also releasing a Spark Client, which help +providing an end-to-end solution for Apache Spark to manage Delta tables using Polaris. + +Note the Polaris Spark Client is able to handle both Iceberg and Delta tables, not just Delta. + +This pages documents how to build and use the Apache Polaris Spark Client before formal release. + +## Prerequisite +1. Check out the polaris repo +```shell +cd ~ +git clone https://github.com/apache/polaris.git +``` +2. Spark with version >= 3.5.3 and <= 3.5.5, recommended with 3.5.5. +```shell +cd ~ +wget https://archive.apache.org/dist/spark/spark-3.5.5/spark-3.5.5-bin-hadoop3.tgz +mkdir spark-3.5 +tar xzvf spark-3.5.5-bin-hadoop3.tgz -C spark-3.5 --strip-components=1 +cd spark-3.5 +``` + +All Spark Client code is available under `plugins/spark` of the polaris repo. + +## Quick Start with Local Polaris Service +If you want to quickly try out the functionality with a local Polaris service, you can follow the instructions +in `plugins/spark/v3.5/getting-started/README.md`. + +The getting-started will start two containers: +1) The `polaris` service for running Apache Polaris using an in-memory metastore +2) The `jupyter` service for running Jupyter notebook with PySpark (Spark 3.5.5 is used) + +The notebook `SparkPolaris.ipynb` provided under `plugins/spark/v3.5/getting-started/notebooks` provides examples +with basic commands, includes: +1) Connect to Polaris using Python client to create Catalog and Roles +2) Start Spark session using the Polaris Spark Client +3) Using Spark to perform table operations for both Delta and Iceberg + +## Start Spark against a deployed Polaris Service +If you want to start Spark with a deployed Polaris service, you can follow the following instructions. + +Before start, Make sure the service deployed is up-to-date, and Spark 3.5 with at least version 3.5.3 is installed. + +### Build Spark Client Jars +The polaris-spark project provides a task createPolarisSparkJar to help building jars for the Polaris Spark client, +The built jar is named as: +`polaris-iceberg-<icebergVersion>-spark-runtime-<sparkVersion>_<scalaVersion>-<polarisVersion>.jar`. + +For example: `polaris-iceberg-1.8.1-spark-runtime-3.5_2.12-0.10.0-beta-incubating-SNAPSHOT.jar`. + +Run the following commands to build a Spark Client jar that is compatible with Spark 3.5 and Scala 2.12. +```shell +cd ~/polaris +./gradlew :polaris-spark-3.5_2.12:createPolarisSparkJar +``` +If you want to build a Scala 2.13 compatible jar, you can use the following command: +- `./gradlew :polaris-spark-3.5_2.13:createPolarisSparkJar` + +The result jar is located at plugins/spark/v3.5/build/<scala_version>/libs after the build. You can also copy the +corresponding jar to any location your Spark will have access. + +### Connecting with Spark Using the built jar +The following CLI command can be used to start the spark with connection to the deployed Polaris service using +the Polaris Spark client jar. + +```shell +bin/spark-shell \ +--jars <path-to-spark-client-jar> \ +--packages org.apache.hadoop:hadoop-aws:3.4.0,io.delta:delta-spark_2.12:3.3.1 \ +--conf spark.sql.extensions=org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions,io.delta.sql.DeltaSparkSessionExtension \ +--conf spark.sql.catalog.spark_catalog=org.apache.spark.sql.delta.catalog.DeltaCatalog \ +--conf spark.sql.catalog.<spark-catalog-name>.warehouse=<polaris-catalog-name> \ +--conf spark.sql.catalog.<spark-catalog-name>.header.X-Iceberg-Access-Delegation=vended-credentials \ +--conf spark.sql.catalog.<spark-catalog-name>=org.apache.polaris.spark.SparkCatalog \ +--conf spark.sql.catalog.<spark-catalog-name>.uri=<polaris-service-uri> \ +--conf spark.sql.catalog.<spark-catalog-name>.credential='<client-id>:<client-secret>' \ +--conf spark.sql.catalog.<spark-catalog-name>.scope='PRINCIPAL_ROLE:ALL' \ +--conf spark.sql.catalog.<spark-catalog-name>.token-refresh-enabled=true +``` + +Replace `path-to-spark-client-jar` to where the built jar is located. The `spark-catalog-name` is the catalog name you +will use with spark, and `polaris-catalog-name` is the catalog name used by Polaris service, for simplicity, you can use +the same name. Replace the `polaris-service-uri`, `client-id` and `client-secret` accordingly, you can refer to +[Quick Start]({{% ref "../0.9.0/quickstart" %}}) for more details about those fields. + +Or you can create a spark session start the connection, following is an example with pyspark +```shell +from pyspark.sql import SparkSession + +spark = SparkSession.builder + .config("spark.jars", <path-to-spark-client-jar>) + .config("spark.jars.packages", "org.apache.hadoop:hadoop-aws:3.3.4,io.delta:delta-spark_2.12:3.3.1") + .config("spark.sql.catalog.spark_catalog", "org.apache.spark.sql.delta.catalog.DeltaCatalog") + .config("spark.sql.extensions", "org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions,io.delta.sql.DeltaSparkSessionExtension") + .config("spark.sql.catalog.<spark-catalog-name>", "org.apache.polaris.spark.SparkCatalog") + .config("spark.sql.catalog.<spark-catalog-name>.uri", <polaris-service-uri>) + .config("spark.sql.catalog.<spark-catalog-name>.token-refresh-enabled", "true") + .config("spark.sql.catalog.<spark-catalog-name>.credential", "<client-id>:<client_secret>") + .config("spark.sql.catalog.<spark-catalog-name>.warehouse", <polaris_catalog_name>) + .config("spark.sql.catalog.polaris.scope", 'PRINCIPAL_ROLE:ALL') + .config("spark.sql.catalog.polaris.header.X-Iceberg-Access-Delegation", 'vended-credentials') + .getOrCreate() +``` +Similar as the CLI command, make sure the corresponding fields are replaced correctly. + +### Create tables with Spark +After the spark is started, you can use it to create and access Iceberg and Delta table like what you are doing before, +for example: +```shell +spark.sql("USE polaris") +spark.sql("CREATE NAMESPACE IF NOT EXISTS DELTA_NS") +spark.sql("CREATE NAMESPACE IF NOT EXISTS DELTA_NS.PUBLIC") +spark.sql("USE NAMESPACE DELTA_NS.PUBLIC") +spark.sql("""CREATE TABLE IF NOT EXISTS PEOPLE ( + id int, name string) +USING delta LOCATION 'file:///tmp/delta_tables/people'; +""") +``` + +## Limitations +The Polaris Spark client has the following functionality limitations: +1) Create table as select (CTAS) is not supported for Delta tables. As a result, the `saveAsTable` method of `Dataframe` + is also not supported, since it relies on the CTAS support. +2) Create a Delta table without explicit location is not supported. +3) Rename a Delta table is not supported. +4) ALTER TABLE ... SET LOCATION/SET FILEFORMAT/ADD PARTITION is not supported for DELTA table. +5) For other non-iceberg tables like csv, there is no specific guarantee provided today. +6) Role-based RBAC support for Delta table write is not available. Create, Drop and List RBAC support is available. Review Comment: What exactly does this mean? Can we just say credential vending isn't supported? Technically the RB in RBAC already stands for Role-based -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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