PostgreSQL-XL, PostgreSQL集群项目(二)

Postgres-XL是一款基于PostgreSQL的可扩展分布式数据库系统,支持SQL标准,具备强大的事务一致性及高并发能力。它适用于OLTP和OLAP场景,通过多版本并发控制实现全局数据一致性,并且能够作为键值存储使用。
Frequently Asked Questions
 

Q. What does XL stand for?

XL is short for eXtensible Lattice. It also connotes an extra large version of PostgreSQL, in this case across multiple systems.

Q. Is this a “NoSQL” solution?

No, Postgres-XL supports traditional SQL, strongly conforms to ANSI SQL:2008, is fully acid, all while being scalable. You can however certainly use it as a key-value store and take advantage of JSON and hstore functionality.

Q. Is the data “sharded”?

Yes. Postgres-XL distributes the data amongst multiple nodes, and, crucially, it ensures a global consistent view of the data thanks to cluster-wide MVCC (Multi-version Concurrency Control) via the Global Transaction Manager component.  Other commercial and non-commercial sharding solutions may not guarantee such consistency and ACID properties.

Q. Are write-intensive applications supported?

Yes, write-intensive applications can take advantage of Postgres-XL running on multiple servers and spreading out the write load. Postgres-XL is well-suited for OLTP.

Q. Are read-heavy applications supported?

Yes, with read-intensive applications data is spread out amongst multiple nodes, effectively giving you more cache and more hardware resources to serve it.  It eliminates the need for other solutions such as memcached.

Q. Are Business Intelligence applications supported?

Yes, Postgres-XL includes Massively Parallel Processing (MPP) capability with sophisticated query planning and inter-node communication that allows it to fulfill query requests over large data sets quickly. Postgres-XL is well suited for Data Warehousing and Data Marts. In Postgres-XL queries are parallelized and the data node nodes communicate with one another directly.

Q. Does one need to take into account that data is split across servers when designing my database schema?

Existing applications will work fine, but for fastest response time, it is helpful to be mindful of data locality. Please see the documentation for more details.  A basic rule of thumb is to distribute (partition) large tables and and tables that are written to frequently, and to replicate tables to all nodes that contain mainly static data.

Q. What kind of client connectivity is offered?

Postgres-XL is wire-level protocol compatible with PostgreSQL.  That means Postgres-XL will work with any PostgreSQL-compatible driver, which includes JDBC, ODBC, OLE DB, Python, Ruby, perl DBI, Tcl, and Erlang.

That also means that many apps written for PostgreSQL will work without modifications against Postgres-XL, even including the well-known pgAdmin utility.

Q. Are geo-distributed database clusters supported?

No, geo-distribution is not natively supported. A Postgres-XL-based solution will depend on your particular requirements, and you should probably engage with a company that is experienced with Postgres-XL.

Q. How does one achieve High Availability?

You can add slaves for each node analogous to PostgreSQL’s streaming replication.   In addition, the cluster can be configured such that the Global Transaction Manager (GTM) can have a GTM Standby.

In terms of automatic failover, it is currently not part of the core project, but Corosync/Pacemaker has been used for this purpose.

Q. Is PostGIS supported?

Yes, PostGIS can be added to Postgres-XL. It has been tested with PostGIS 2.0.

Q. How does Postgres-XL relate to StormDB?

Postgres-XL is the core of TransLattice Storm (StormDB) rebranded and open sourced.

Q. How does Postgres-XL relate to Postgres-XC and Stado?

The project includes architects and developers who previously worked on both Postgres­-XC and Stado, and Postgres-XL contains code from Postgres-­XC.

The Postgres-XL project has its own philosophy and approach.

Postgres-XL values stability, correctness and performance over new functionality. The Postgres-XL project ultimately strives to track and merge in code from PostgreSQL.

Postgres-XL adds some significant performance improvements like MPP parallelism and replan avoidance on the data nodes that are not part of Postgres­-XC. Postgres-­XC currently focuses on OLTP workloads. Postgres-XL is more flexible in terms of the types of workloads it can handle including Big Data processing thanks to its parallelism.  Additionally, Postgres-XL is more secure for multi­-tenant environments.

The Postgres-XL community is also very open and welcoming to those who wish to become more involved and contribute, whether on the mailing lists, participating in developer meetings, or meeting in person.  Users will help drive development priorities and the project roadmap.

<think>我们正在配置一个PostgreSQL-XL集群,涉及两台Ubuntu服务器,需要同步2TB的数据。PostgreSQL-XL是一个基于PostgreSQL的分布式数据库,适用于大规模数据分析和事务处理。以下是最佳实践和配置教程:###1.环境准备-**硬件要求**:确保两台服务器有足够的存储空间(至少2.5TB,考虑冗余和增长),建议使用SSD以提高I/O性能。-**网络要求**:服务器间网络带宽至少1Gbps,低延迟(<1ms),配置主机名解析(/etc/hosts)并禁用防火墙或开放端口(默认5432)。-**软件要求**:-Ubuntu20.04LTS或22.04LTS-PostgreSQL-XL10(稳定版本)###2.安装PostgreSQL-XL在两台服务器上执行相同的安装步骤:```bash#创建用户和目录sudoadduserpostgressudomkdir-p/home/postgres/pgxlsudochown-Rpostgres:postgres/home/postgres#切换到postgres用户sudosu-postgres#解压并编译安装(假设源码包在/home/postgres目录下)tar-zxvfpostgres-xl-10r1.tar.gzcdpostgres-xl-10r1./configure--prefix=/home/postgres/pgxlmake&&makeinstall```>注意:确保两台服务器上的安装路径一致[^1]。###3.配置集群假设两台服务器IP为`192.168.1.101`(节点1,作为GTMMaster和Coordinator)和`192.168.1.102`(节点2,作为Datanode)。####节点1配置(GTMMaster+Coordinator)-**GTMMaster配置**(`/home/postgres/pgxl/gtm/gtm.conf`):```confnodename='gtm_master'listen_addresses='*'port=6666```-**Coordinator配置**(`/home/postgres/pgxl/coord/postgresql.conf`):```confport=5432listen_addresses='*'gtm_host='192.168.1.101'gtm_port=6666```####节点2配置(Datanode)-**Datanode配置**(`/home/postgres/pgxl/datanode/postgresql.conf`):```confport=5432listen_addresses='*'gtm_host='192.168.1.101'gtm_port=6666```###4.初始化并启动集群-**节点1(启动GTMMaster)**:```bashgtm_ctlinit-D/home/postgres/pgxl/gtmgtm_ctlstart-D/home/postgres/pgxl/gtm```-**节点1(初始化并启动Coordinator)**:```bashinitdb-D/home/postgres/pgxl/coordpg_ctlstart-D/home/postgres/pgxl/coord```-**节点2(初始化并启动Datanode)**:```bashinitdb-D/home/postgres/pgxl/datanodepg_ctlstart-D/home/postgres/pgxl/datanode```###5.创建集群节点关系在Coordinator(节点1)上执行:```sql--添加Datanode(节点2)CREATENODEdatanode1WITH(TYPE='datanode',HOST='192.168.1.102',PORT=5432);--激活节点SELECTpgxc_node_reload();```###6.数据同步策略(2TB数据)-**初始数据加载**:使用`pg_dump`和`pg_restore`从现有数据库导入,或使用`COPY`命令批量导入CSV文件。```bash#在Coordinator上导入数据psql-dpostgres-c"COPYlarge_tableFROM'/path/to/data.csv'DELIMITER','CSV;"```-**分布式表设计**:根据数据特点选择分片键(如时间戳或ID),创建分布式表:```sqlCREATETABLElarge_table(...)DISTRIBUTEBYHASH(id);--按ID哈希分布```-**实时同步**:PostgreSQL-XL自动处理写入同步,确保跨节点一致性。###7.性能优化-**并行查询**:协调节点并行查询各数据节点。-**连接池**:使用PgBouncer减少连接开销。-**分区表**:对超大表按时间范围分区。###8.监控与维护-**监控工具**:使用`pg_stat_activity`和`pgxc_stat_activity`监控查询。-**备份策略**:使用`pg_basebackup`定期备份每个节点。###注意事项1.**时间同步**:使用NTP服务确保服务器时间一致。2.**定期维护**:执行`VACUUMANALYZE`优化性能。3.**故障转移**:配置GTM备用节点(可选)。>提示:大规模数据导入时,禁用索引并在导入后重建可加速过程[^1]。§§相关问题§§1.PostgreSQL-XLPostgreSQL的主要区别是什么?2.如何扩展PostgreSQL-XL集群到更多节点?3.PostgreSQL-XL支持哪些数据分片策略?4.如何监控PostgreSQL-XL集群的性能?5.PostgreSQL-XL中如何处理节点故障?</think>### PostgreSQL-XL 在两台 Ubuntu 服务器间同步 2TB 数据的完整配置指南 #### 一、环境准备(两台服务器执行相同操作) ```bash # 创建专用用户和目录 sudo adduser postgres sudo mkdir -p /home/postgres/pgxl/{data,gtm,coord,datanode} sudo chown -R postgres:postgres /home/postgres # 安装依赖 sudo apt update sudo apt install -y build-essential libreadline-dev zlib1g-dev flex bison # 下载源码(版本需一致) wget https://sourceforge.net/projects/postgres-xl/files/postgres-xl-10r1.tar.gz sudo mv postgres-xl-10r1.tar.gz /home/postgres/ sudo chown postgres:postgres /home/postgres/postgres-xl-10r1.tar.gz ``` #### 、编译安装 PostgreSQL-XL ```bash sudo su - postgres tar -zxvf postgres-xl-10r1.tar.gz cd postgres-xl-10r1 # 编译配置(两台服务器相同参数) ./configure --prefix=/home/postgres/pgxl \ --with-python \ --with-openssl # 编译安装 make -j$(nproc) make install ``` #### 三、集群架构设计(2节点) | 节点类型 | 服务器1 (192.168.1.101) | 服务器2 (192.168.1.102) | |----------------|-------------------------------|-------------------------------| | **GTM** | Master | Standby | | **Coordinator**| 主协调节点 | 备用协调节点 | | **Datanode** | 数据节点1 (存储1TB) | 数据节点2 (存储1TB) | #### 四、配置文件设置 **1. GTM Master (服务器1: `/home/postgres/pgxl/gtm/gtm.conf`)**: ```conf nodename = 'gtm_master' listen_addresses = '*' port = 6666 log_file = 'gtm.log' ``` **2. Coordinator (服务器1: `/home/postgres/pgxl/coord/postgresql.conf`)**: ```conf port = 5432 listen_addresses = '*' gtm_host = '192.168.1.101' gtm_port = 6666 shared_buffers = 16GB # 根据内存调整 ``` **3. Datanode (服务器2: `/home/postgres/pgxl/datanode/postgresql.conf`)**: ```conf port = 15432 listen_addresses = '*' gtm_host = '192.168.1.101' gtm_port = 6666 max_connections = 500 ``` > **关键**:所有节点的`pg_hba.conf`添加: ```conf host all all 192.168.1.0/24 trust ``` #### 五、初始化并启动集群 **服务器1 (GTM Master + Coordinator)**: ```bash # 初始化GTM gtm_ctl init -D /home/postgres/pgxl/gtm gtm_ctl start -D /home/postgres/pgxl/gtm # 初始化Coordinator initdb -D /home/postgres/pgxl/coord pg_ctl start -D /home/postgres/pgxl/coord ``` **服务器2 (Datanode)**: ```bash initdb -D /home/postgres/pgxl/datanode pg_ctl start -D /home/postgres/pgxl/datanode ``` #### 六、配置数据同步与分片 **在Coordinator节点操作**: ```sql -- 添加数据节点 CREATE NODE datanode1 WITH (TYPE = 'datanode', HOST = '192.168.1.102', PORT = 15432); -- 创建分布式表(按范围分片) CREATE TABLE bigdata ( id BIGSERIAL PRIMARY KEY, data JSONB ) DISTRIBUTE BY RANGE (id); -- 分配2TB存储空间(各节点1TB) ALTER NODE datanode1 SET (DATA DIRECTORY = '/home/postgres/pgxl/datanode'); ``` #### 七、数据加载优化(2TB数据处理) ```bash # 并行加载(使用dblink扩展) pg_bulkload -d postgres -h 192.168.1.101 -U postgres \ -i /path/to/data.csv \ -o "PARALLEL=ON, TYPE=CSV, DELIMITER=','" # 分批次导入脚本示例 for i in {1..10}; do psql -c "COPY bigdata FROM '/data/chunk_$i.csv' DELIMITER ',' CSV" done ``` #### 八、性能调优参数 ```conf # postgresql.conf 关键优化 work_mem = 256MB maintenance_work_mem = 2GB effective_cache_size = 48GB # 系统内存的70% checkpoint_completion_target = 0.9 max_wal_size = 32GB ``` #### 九、监控与维护 ```bash # 查看集群状态 psql -c "SELECT * FROM pgxc_node" # 数据分布检查 SELECT xc_node_id, count(*) FROM bigdata GROUP BY xc_node_id; # 自动备份(每天全备) pg_basebackup -h 192.168.1.101 -D /backup/full_$(date +%F) ``` > **最佳实践**: > 1. 使用SSD存储提升I/O性能 > 2. 配置千兆/万兆专用同步网络 > 3. 定期执行`VACUUM ANALYZE` > 4. 启用WAL归档(`archive_mode = on`) #### 十、故障转移配置 ```bash # GTM Standby (服务器2) gtm_ctl init -D /home/postgres/pgxl/gtm_standby -Z standby gtm_ctl register -D /home/postgres/pgxl/gtm_standby -Z standby \ -p 6666 -h 192.168.1.101 ``` --- ### 常见问题解决方案 1. **数据倾斜问题**: ```sql -- 重新分布数据 ALTER TABLE bigdata DISTRIBUTE BY MODULO (hash_column); ``` 2. **同步延迟监控**: ```sql SELECT pg_last_xact_replay_timestamp() - pg_last_committed_xact(); ``` 3. **连接池配置**: 使用`pgbouncer`管理连接: ```ini [databases] postgres = host=192.168.1.101 port=5432 dbname=postgres ``` > 完整文档参考:[PostgreSQL-XL 官方指南](https://www.postgres-xl.org/documentation/)
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