Pivotal Greenplum©for Kubernetes: Demonstration of Managing Greenplum Database on Kubernetes Massive Parallel Processing Relational Database in the Cloud

被引：1

作者：

Patel, Jemish ^{[1
]}

Tadi, Goutam ^{[1
]}

Basarir, Oz ^{[1
]}

Hamel, Lawrence ^{[1
]}

Sharp, David ^{[1
]}

Yang, Fei ^{[1
]}

Zhang, Xin ^{[1
]}

机构：

[1] Pivotal Software, San Francisco, CA 94103 USA

来源：

SIGMOD '19: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA | 2019年

关键词：

D O I：

10.1145/3299869.3320229

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Greenplum Database (GPDB) has many features designed to enable data scientists. Before a data scientist can use GPDB, a database administrator (DBA) must provision a cluster and install any required data science packages. Provisioning a GPDB cluster on bare metal requires a lengthy setup process. Scaling, recovering, and securing the cluster post-deployment are also complex. Greenplum for Kubernetes (GP4K) abstracts away these complexities, simplifying and automating the process for users. In this demonstration, we introduce GP4K with an opinionated deployment and a declarative manifest. We provide a brief overview of GP4K's architecture and discuss its implementation. We also demonstrate a full life cycle of managing a cluster from birth to retirement, including scale-up and self-healing all with minimal DBA inputs, as shown in a video here.(1)

引用

页码：1969 / 1972

页数：4

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