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Java API
Iceberg Java API Tables The main purpose of the Iceberg API is to manage table metadata, like schema, partition spec, metadata, and data files that store table data. Table metad... -
Java Quickstart
Java API Quickstart Create a table Tables are created using either a Catalog or an implementation of the Tables interface. Using a Hive catalog The Hive catalog connects to... -
第四章：线程安全问题
学习目标 1. 什么是线程安全 1.1 线程安全的定义 1.2 线程安全的重要性 2. 共享资源访问的竞态条件 2.1 什么是竞态条件 2.2 竞态条件示例 2.3 竞态条件的类型 读-改-写竞态条件 检查再执行竞态条件 3. 线程安全问题的表现形式 3.1 原子性问题 3.2 可见性问题 3.3 有序性问题 4. 实战案例：商品... -
第六章：volatile关键字
学习目标 1 内存可见性问题 1.1 什么是内存可见性 1.2 内存可见性问题的原因 2 volatile的作用与使用场景 2.1 volatile关键字介绍 2.2 volatile的内存语义 2.3 volatile的适用场景 2.4 volatile不能解决的问题 3 volatile与synchronized的区别 3.1 可见性与... -
Writes
Spark Writes To use Iceberg in Spark, first configure Spark catalogs . Some plans are only available when using Iceberg SQL extensions in Spark 3. Iceberg uses Apache Spark’s D... -
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... -
DDL
Spark DDL To use Iceberg in Spark, first configure Spark catalogs . Iceberg uses Apache Spark’s DataSourceV2 API for data source and catalog implementations. CREATE TABLE Spark... -
第五章：synchronized关键字
学习目标 1. 对象锁与类锁的概念 1.1 对象锁（实例锁） 1.2 类锁（静态锁） 1.3 对象锁与类锁的对比 2. synchronized修饰方法与代码块的区别 2.1 修饰方法 vs 修饰代码块 2.2 不同锁对象的选择 3. synchronized的底层实现原理 3.1 Monitor监视器 3.2 字节码层面的实现 3.3 ... -
Java Custom Catalog
Custom Catalog It’s possible to read an iceberg table either from an hdfs path or from a hive table. It’s also possible to use a custom metastore in place of hive. The steps to do... -
Distributed counters
Id generator Redis or Valkey based Java Id generator RIdGenerator generates unique numbers but not monotonically increased. At first request, batch of id numbers is allocated and...
