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Hive Metastore
Syncing to Hive Metastore This document walks through the steps to register an Apache XTable™ (Incubating) synced table on Hive Metastore (HMS). Pre-requisites Source table(s) ... -
5. Data partitioning (sharding)
1. Partitioning (sharding) of Redis based Java objects 2. Partitioning (sharding) of Redis setup This feature available only in Redisson PRO edition. 1. Partitioning (shardin... -
Variable Management
Background Introduction Create Variable Reference variables in Flink SQL Reference variables in args of Flink JAR jobs Background Introduction In the actual production enviro... -
Maintenance
Maintenance Maintenance operations require the Table instance. Please refer Java API quickstart page to refer how to load an existing table. Recommended Maintenance Expire... -
Performance
Scan planning Metadata filtering Data filtering Iceberg is designed for huge tables and is used in production where a single table can contain tens of petabytes of data. Even ... -
Schedulers
Introduction Quartz Azkaban Oozie Launching Gobblin in Local Mode Example Config Files Uploading Files to HDFS Adding Gobblin jar Dependencies Launching the Job Launching ... -
Distributed objects
Object holder Java implementation of Redis or Valkey based RBucket object is a holder for any type of object. Size is limited to 512Mb. Code example: RBucket < AnyObject > buc... -
FAQs
Gobblin General Questions What is Gobblin? What programming languages does Gobblin support? Does Gobblin require any external software to be installed? What Hadoop versions can ... -
Introduction
Documentation Apache Iceberg is an open table format for huge analytic datasets. Iceberg adds tables to compute engines including Spark, Trino, PrestoDB, Flink, Hive and Impala u... -
Seatunnel runs on Flink
Set Flink configuration information in the job How to set up a simple Flink job How to run a job in a project Flink is a powerful high-performance distributed stream processing...
