《深入理解Greenplum数据库：基于MPP架构的大数据处理》 Greenplum数据库系统，作为一款高效的大数据处理工具，被广泛应用于大数据仓库（DW）和商业智能（BI）领域。其核心特性在于采用无共享（shared-nothing）的大规模并行处理（MPP）架构，这使得它在处理海量数据时展现出卓越的性能和扩展性。在本文中，我们将深入探讨Greenplum的MPP架构、与PostgreSQL的关系以及如何在RHEL7环境下安装和使用Greenplum。 让我们了解MPP架构。MPP（Massively Parallel Processing）是一种分布式计算模型，每个节点都拥有独立的内存和存储资源，且不共享这些资源。在Greenplum中，数据被分割成多个段，均匀分布在各个节点上，每个节点独立处理分配到的数据，然后将结果合并。这种架构使得Greenplum能充分利用硬件资源，实现快速的数据处理和分析。 Greenplum是基于PostgreSQL的，这意味着它继承了PostgreSQL的SQL兼容性和ACID事务特性。然而，Greenplum针对大规模数据处理进行了优化，如增加并行查询执行、动态数据分片等。同时，Greenplum还提供了高级的数据分析功能，如并行化的数据加载、复杂的SQL查询支持和高级统计函数。 在“greenplum-db-5.0.0-rhel7-x86_64.zip”压缩包中，我们看到一个名为“greenplum-db-5.0.0-rhel7-x86_64.bin”的可执行文件。这是Greenplum数据库的安装程序，适用于Red Hat Enterprise Linux 7（RHEL7）64位环境。安装过程通常包括以下步骤： 1. 解压下载的zip文件。 2. 执行安装脚本，通常需要root权限。 3. 配置系统环境变量，如设置`$GPHOME`和`$PATH`。 4. 初始化数据库集群，定义数据目录和初始化参数。 5. 创建管理员用户和数据库。 6. 配置安全设置，如防火墙规则和SSL证书（如果需要）。 7. 测试连接和运行简单的查询，验证安装成功。 在实际应用中，Greenplum的高效性能得益于其智能查询优化器。它能够分析SQL语句，生成最佳的执行计划，利用MPP架构的优势，使得数据处理速度得到显著提升。此外，Greenplum还支持分区表、物化视图和并行加载等功能，进一步增强了其在大数据场景下的实用性。 Greenplum数据库是大数据工程师不可或缺的工具，它的MPP架构和对PostgreSQL的优化使其在大数据处理领域独树一帜。掌握Greenplum的安装、配置和使用，将极大地提升数据处理和分析的能力，对于数据驱动的企业来说具有重要的价值。

Greenplum 大数据平台基于MPP（大规模并行处理）架构，具有良好的弹性和线性扩展能力，内置并行存储、并行通讯、并行计算和优化技术，兼容 SQL 标准，具备强大、高效、安全的PB级结构化、半结构化和非结构化数据存储、处理和实时分析能力 rpm安装包，直接安装，很方便，有需要可以下载试一下，

greenplum-db-5.22.0-rhel7-x86_64.rpm greenplum-db-5.22.0-rhel7-x86_64.rpm greenplum-db-5.22.0-rhel7-x86_64.rpm

Greenplum是一个面向数据仓库应用的关系型数据库,它基于流行的PostgreSQL开发,因为有良好的体系结构,所以在数据存储,高并发,高可用,线性扩展,反应速度,易用性和性价比等方面有非常明显的优势,非常受欢迎.进入大数据时代以后,Greenplum的性能在TB级别数据量的表现上非常优秀,单机性能相比Hadoop要快上好几倍;在功能和语法上,要比Hadoop上的SQL引擎Hive好用很多,普通用户更加容易上手.

Greenplum 6 exporter for Prometheus of realtime monitor system

官网下载greenplum6.27最新版本，，适配centos7、redhat7、anolis os7.9

postgresql-9.3-1102-jdbc41.jar greenplum-connector-apache-spark-scala_2.11-2.1.0.jar PROGRESS_DATADIRECT_JDBC_DRIVER_PIVOTAL_GREENPLUM_6.0.0.000181.jar

Greenplum作为一款高性能、大规模并行处理（MPP）的数据库，VMware被博通收购之后，之前的Greenplum下载地址也发生了改变，为了方便大家使用，故整理了好了最新的安装包，本压缩包中包含greenplum-db-7.2.0-el9-x86_64和greenplum-db-7.1.0-el8-x86_64两个软件包，软件包中仅包含DB的软件，不涉及到其他的软件，本软件仅适合于个人测试使用，不可使用商业使用。博通下载地址请参考： https://knowledge.broadcom.com/external/article?articleNumber=371153

greenplum-db-6.2.1-rhel7-x86_64.rpm Pivotal Greenplum 6.2 Release Notes This document contains pertinent release information about Pivotal Greenplum Database 6.2 releases. For previous versions of the release notes for Greenplum Database, go to Pivotal Greenplum Database Documentation. For information about Greenplum Database end of life, see Pivotal Greenplum Database end of life policy. Pivotal Greenplum 6 software is available for download from the Pivotal Greenplum page on Pivotal Network. Pivotal Greenplum 6 is based on the open source Greenplum Database project code. Important: Pivotal Support does not provide support for open source versions of Greenplum Database. Only Pivotal Greenplum Database is supported by Pivotal Support. Release 6.2.1 Release Date: 2019-12-12 Pivotal Greenplum 6.2.1 is a minor release that includes new features and resolves several issues. New Features Greenplum Database 6.2.1 includes these new features: Greenplum Database supports materialized views. Materialized views are similar to views. A materialized view enables you to save a frequently used or complex query, then access the query results in a SELECT statement as if they were a table. Materialized views persist the query results in a table-like form. Materialized view data cannot be directly updated. To refresh the materialized view data, use the REFRESH MATERIALIZED VIEW command. See Creating and Managing Materialized Views. Note: Known Issues and Limitations describes a limitation of materialized view support in Greenplum 6.2.1. The gpinitsystem utility supports the --ignore-warnings option. The option controls the value returned by gpinitsystem when warnings or an error occurs. If you specify this option, gpinitsystem returns 0 if warnings occurred during system initialization, and returns a non-zero value if a fatal error occurs. If this option is not specified, gpinitsystem returns 1 if initialization completes with warnings, and returns value of 2 or greater if a fatal error occurs. PXF version 5.10.0 is included, which introduces several new and changed features and bug fixes. See PXF Version 5.10.0 below. PXF Version 5.10.0 PXF 5.10.0 includes the following new and changed features: PXF has improved its performance when reading a large number of files from HDFS or an object store. PXF bundles newer tomcat and jackson libraries. The PXF JDBC Connector now supports pushdown of OR and NOT logical filter operators when specified in a JDBC named query or in an external table query filter condition. PXF supports writing Avro-format data to Hadoop and object stores. Refer to Reading and Writing HDFS Avro Data for more information about this feature. PXF is now certified with Hadoop 2.x and 3.1.x and Hive Server 2.x and 3.1, and bundles new and upgraded Hadoop libraries to support these versions. PXF supports Kerberos authentication to Hive Server 2.x and 3.1.x. PXF supports per-server user impersonation configuration. PXF supports concurrent access to multiple Kerberized Hadoop clusters. In previous releases of Greenplum Database, PXF supported accessing a single Hadoop cluster secured with Kerberos, and this Hadoop cluster must have been configured as the default PXF server. PXF introduces a new template file, pxf-site.xml, to specify the Kerberos and impersonation property settings for a Hadoop or JDBC server configuration. Refer to About Kerberos and User Impersonation Configuration (pxf-site.xml) for more information about this file. PXF now supports connecting to Hadoop with a configurable Hadoop user identity. PXF previously supported only proxy access to Hadoop via the gpadmin Greenplum user. PXF version 5.10.0 deprecates the following configuration properties. Note: These property settings continue to work. The PXF_USER_IMPERSONATION, PXF_PRINCIPAL, and PXF_KEYTAB settings in the pxf-env.sh file. You can use the pxf-site.xml file to configure Kerberos and impersonation settings for your new Hadoop server configurations. The pxf.impersonation.jdbc property setting in the jdbc-site.xml file. You can use the pxf.service.user.impersonation property to configure user impersonation for a new JDBC server configuration. Note: If you have previously configured a PXF JDBC server to access Kerberos-secured Hive, you must upgrade the server definition. See Upgrading PXF in Greenplum 6.x for more information. Changed Features Greenplum Database 6.2.1 includes these changed features: Greenplum Stream Server version 1.3.1 is included in the Greenplum distribution. Resolved Issues Pivotal Greenplum 6.2.1 is a minor release that resolves these issues: 29454 - gpstart During Greenplum Database start up, the gpstart utility did not report when a segment instance failed to start. The utility always displayed 0 skipped segment starts. This issue has been resolved. gpstart output was also enhanced to provide additional warnings and summary information about the number of skipped segments. For example: [WARNING]:-********

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