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Articles by - Sql
Inside StarRocks: Why Joins Are Faster Than You’d Expect
Some additional information in one line ✍🏼 About The Author: Seaven He, StarRocks Committer, Engineer at Celerdata Joins are the hardest part of OLAP. Many systems can’t run them efficiently at scale, so teams denormalize into wide tables instead, 10× their storage, dealing with complex stream processing pipelines, and painfully slow and expensive schema evolution that triggers large backfills.
sql developer v4 how to extract schema - user creation ddl ?
A reader, November 26, 2015 - 6:30 am UTC I tried your suggestion, it didnt work. I am looking for user creation script generation for a list of selective users. Create like does not give me any script option. Is this simple task impossible in sql developer ? I am really shocked ? I know it should be there somewhere, need to find it. I hope the makers of sql developer are listening. Why they make such a simple Task so difficult apart from my ignorance of this user-not-at-all-friendly tool?
如何充分发挥 SQL 能力?-阿里云开发者社区
来源|阿里云开发者公众号 作者|里戈 1.1 初衷 如何高效地使用 MaxCompute(ODPS)SQL ,将基础 SQL 语法运用到极致。 在大数据如此流行的今天,不只是专业的数据人员,需要经常地跟 SQL 打交道,即使是产品、运营等非技术同学,也会或多或少地使用到 SQL ,如何高效地发挥 SQL 的能力,继而发挥数据的能力,变得尤为重要。MaxCompute(ODPS)SQL?发展到今天已经颇为成熟,作为一种 SQL 方言,其 SQL 语法支持完备,具有非常丰富的内置函数,支持开窗函数、用户自定义函数、用户自定义类型等诸多高级特性,可以高效地应用在各种数据处理场景。如何充分发挥 SQL 能力,是本篇文章的主题。本文尝试独辟蹊径,强调通过灵活的、发散性的数据处理思维,就可以用最基础的语法,解决复杂的数据场景。 1.2 适合人群 不论是初学者还是资深人员,本篇文章或许都能有所帮助,不过更适合中级、高级读者阅读。 本篇文章重点介绍数据处理思维,并没有涉及到过多高阶的语法,同时为了避免主题发散,文中涉及的函数、语法特性等,不会花费篇幅进行专门的介绍,读者可以按自身情况自行了解。...
基于 Flink CDC 构建 MySQL 和 Postgres 的 Streaming ETL
官方网址:https://ververica.github.io/flink-cdc-connectors/release-2.3/content/%E5%BF%AB%E9%80%9F%E4%B8%8A%E6%89%8B/mysql-postgres-tutorial-zh.html官方教程有些坑,经过自己实测,记录个笔记。 服务器环境: VM虚拟机:CentOS7.9 docker版本:Docker version 24.0.5, build ced0996 docker compose 版本:2.19 jdk 1.8 虚拟机IP:192.168.122.131 内存:16G(一定要大于等于16G) CPU:4g 磁盘 :>= 60G DOCKER_CONFIG=${DOCKER_CONFIG:-/usr/local/lib/docker/cli-plugins} mkdir -p $DOCKER_CONFIG/cli-plugins curl -SL...
最新版Flink CDC MySQL同步Elasticsearch(一)
1.环境准备 首先我们要基于Flink CDC MySQL同步MySQL的环境基础上(flink-1.17.1、Java8、MySQL8)搭建Elasticsearch7-17-10和Kibana 7.17.10。笔者已经搭建好环境,这里不做具体演示了,如果需要Es的搭建教程情况笔者其他博客 2.编译flink-sql-connector-mysql-cdc 最新版本flink-1.17.1 mysql同步Es具体jar依赖版本如下所示: flink-sql-connector-elasticsearch7-3.0.1-1.17.jar flink-sql-connector-mysql-cdc-2.5-SNAPSHOT.jar(需要自行进行构建编译,笔者构建的已经上次至次博客。需要可以进行下载,csdn需要积分下载,无法设置免费的,需要免费版可以直接联系笔者) 下载所需的JAR包并放在下面flink-1.17.1/lib/: git clone https://github.com/ververica/flink-cdc-connectors.git cd...
最新版Flink CDC MySQL同步MySQL(一)
1.概述 Flink CDC 是Apache Flink ®的一组源连接器,使用变更数据捕获 (CDC) 从不同数据库中获取变更。Apache Flink 的 CDC Connectors集成 Debezium 作为捕获数据更改的引擎。所以它可以充分发挥 Debezium 的能力。 2.支持的连接器 连接器数据库驱动 mongodb-cdc MongoDB: 3.6, 4.x, 5.0 MongoDB Driver: 4.3.4 mysql-cdc MySQL: 5.6, 5.7, 8.0.x、RDS MySQL: 5.6, 5.7, 8.0.x、PolarDB MySQL: 5.6, 5.7, 8.0.x、Aurora MySQL: 5.6, 5.7, 8.0.x、MariaDB: 10.x、PolarDB X: 2.0.1 JDBC Driver: 8.0.28 oceanbase-cdc OceanBase CE: 3.1.x, 4.x、OceanBase EE: 2.x, 3.x, 4.x OceanBase Driver: 2.4.x oracle-cdc...
Migrate data from partitioned tables in PostgreSQL using AWS DMS | Amazon Web Services
Migrating workloads from PostgreSQL to a data warehouse like Amazon Redshift can pose challenges during the change data capture (CDC) phase when dealing with partitioned tables. In this post, we illustrate how we can migrate data from PostgreSQL partitioned tables to a single table on the target database using AWS Database Migration Service (AWS DMS). We use Amazon Redshift as our target endpoint.
如何充分发挥 SQL 能力?_ITPUB博客
来源:阿里云开发者 阿里妹导读 如何充分发挥 SQL 能力,是本篇文章的主题。本文尝试独辟蹊径,强调通过灵活的、发散性的数据处理思维,就可以用最基础的语法,解决复杂的数据场景。 一、前言 1.1 初衷 如何高效地使用 MaxCompute(ODPS)SQL ,将基础 SQL 语法运用到极致。 在大数据如此流行的今天,不只是专业的数据人员,需要经常地跟 SQL 打交道,即使是产品、运营等非技术同学,也会或多或少地使用到 SQL ,如何高效地发挥 SQL 的能力,继而发挥数据的能力,变得尤为重要。MaxCompute(ODPS)SQL 发展到今天已经颇为成熟,作为一种 SQL 方言,其 SQL 语法支持完备,具有非常丰富的内置函数,支持开窗函数、用户自定义函数、用户自定义类型等诸多高级特性,可以高效地应用在各种数据处理场景。如何充分发挥 SQL 能力,是本篇文章的主题。本文尝试独辟蹊径,强调通过灵活的、发散性的数据处理思维,就可以用最基础的语法,解决复杂的数据场景。 1.2 适合人群 不论是初学者还是资深人员,本篇文章或许都能有所帮助,不过更适合中级、高级读者阅读。...
Translating SQL into Python -Part 1
Image by Author If you are sick of struggling with the corresponding syntax for SQL in Python, then you are in the right place. The ability to write in both not only makes you more attractive to clients or employers, but it can also save you shed loads of time by enabling you to write more efficient, streamlined data processes.
Guru: Use SQL To Replace Reports
June 14, 2021 Ted Holt Does anybody write report programs anymore? If so, why? Reports are so twentieth-century. The people we serve want spreadsheets, Web pages, cell-phone apps and other modern conveniences. What we need is an easy way to make our report programs write the same information to modern interfaces without having to perform major surgery on them. Some 10 years or so ago, I built a scripting language to enable me to reformat spooled files into stream files in CSV format.
Guru: Generate SQL for Dependents
May 24, 2021 Paul Tuohy Way back in October 2014, in the article Find A View Of A View Of A View. . ., I detailed a stored procedure that, given the name of a table or a view, provides the full list of dependent views and all of their dependents and all of their dependents, etc. This is a stored procedure that has served me well in the world of DDL, where it is common to have views of views of views.
Easily Clone your Delta Lake for Testing, Sharing, and ML Reproducibility
Introducing Clones An efficient way to make copies of large datasets for testing, sharing and reproducing ML experiments We are excited to introduce a new capability in Databricks Delta Lake – table cloning. Creating copies of tables in a data lake or data warehouse has several practical uses. However, given the volume of data in tables in a data lake and the rate of its growth, making physical copies of tables is an expensive operation.
Pl Sql Dynamic Table Name In Select
Explore how to use dynamic table names in PL/SQL SELECT statements effectively with Dynamic SQL Modification Techniques. The framework for autonomous intelligence When working with dynamic table names in PL/SQL, it is essential to understand how to construct your SQL queries effectively. Dynamic SQL allows you to build SQL statements at runtime, which is particularly useful when the table name is not known until execution.
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