为什么需要分布式数据库
有很多原因数据库需要扩展性。1、请求需要访问的数据量过大（单纯的数据量大不是理由，例如从不访问，归档即可）；2、服务器CPU、内存、网络、IO到了瓶颈，响应时间大大下降；3、MPP中，集中式数据库在设计时通常为了开发人员使用更加顺畅和丝滑，尽可能的让数据库设计和SQL非常简单，比如不需要指定某些表实际上是存在主外键关系，从而导致并行执行效果打折；或者并行执行在一开始并不包含，后面逐渐增强，导致并行执行有天然的缺陷，分区亦如此。这三通常是根本原因。
Citus介绍
首先提供了比较公正参考的是citus中国写的一篇文章PG-XL，Citus，GreenPlum如何选择，不同于其他分布式数据库如tidb、oceanbase、tdsql等每家都说自己最厉害，citus还是比较客观的分析，它自己比较适合于OLTP下的分布式，并不适合于大规模的adhoc场景。实际上很多系统数据量积累的比较大、同时业务流程又很复杂，但是TPS不高，这些系统要应用于分布式数据库，物理模型的设计是很重要的，不是简单的库能套上去的，例如数据中心、历史库的包含就很重要了。亦或者上去了就下不来了，维护成本会非常高。
和其他分布式架构一样，citus也采用协调者和工作者节点，也可以认为是master和worker，说计算和存储分离是不合适的（大多数分布式数据库如oceanbase、goldendb、TDSQL自称计算和存储分离也是不合适的）。真正接近了存储和计算分离的是oracle exadata、tidb。如下所示，协调者和工作者一样都是postgresql实例。
SQL语句经过语法解析后，在协调者节点的analyze阶段被citus扩展（和greenplum、xl、xc不同的是，citus采用的是extension机制（pg定义了大量hook供各种extension访问，具体可参见postgresql内核开发必备之extension机制））替换，并进行SQL语句的fork and join过程。得益于extension这一点，你可以认为citus本质上和greenplum、xl以及xc在事务、语法语义等数据库本身特性的支持上是差不多的。而不是三方中间件如pgpool、pgbouncer中的硬塞实现。因此具有更好的一致性和稳定性保证。
在分布式事务的实现上，citus也是采用2PC协议。它的实现可以参考http://citusdb.cn/?p=661。
注：citus架构的优点在于，它认为分布式是一个特性，而不是属性。这一点LZ在所有场合都是这么坚信，95%+的系统永远都不需要微服务架构，数据库也不需要分布式，因为其到不了那个容量，所以理论上可以扩展使得应用能够同时运行于单实例和分布式，而其它一开始就设计为分布式的数据库是很难的。
因为没有做单独GTM节点的概念，citus无法的协调者无法实现多活，这种情况下容易出现协调者单点，如下：
对此，Citus还提供了两个参数use_secondary_node和writable_standby_coordinator以支持写入能力扩展及数据节点读写分离。这样standby cn也可以执行查询和DML操作。如下所示：
由此可见，可靠的分布式数据库架构是非常复杂的，如果没有非常一体化的监控管理平台，其维护难度可想而知。
参考：https://blog.csdn.net/weixin_46199817/article/details/117223870
Citus安装
可以从https://github.com/citusdata/citus下载源码或rpm，一般用户可以选择yum install citus101_13-10.1.1.citus-1.el7.x86_64。
[zjh@lightdb1 usr]$ rpm -ql postgresql13-13.3-1PGDG.rhel7.x86_64 /usr/pgsql-13/bin/clusterdb /usr/pgsql-13/bin/createdb /usr/pgsql-13/bin/createuser /usr/pgsql-13/bin/dropdb /usr/pgsql-13/bin/dropuser /usr/pgsql-13/bin/pg_basebackup /usr/pgsql-13/bin/pg_config /usr/pgsql-13/bin/pg_dump /usr/pgsql-13/bin/pg_dumpall [zjh@lightdb1 usr]$ rpm -qa | grep citus citus_13-10.0.3-1.rhel7.x86_64 r[zjh@lightdb1 usr]$ rpm -ql citus_13-10.0.3-1.rhel7.x86_64 /usr/pgsql-13/doc/extension/README-citus.md /usr/pgsql-13/lib/citus.so /usr/pgsql-13/share/extension/citus--10.0-1--10.0-2.sql /usr/pgsql-13/share/extension/citus--10.0-2--10.0-3.sql /usr/pgsql-13/share/extension/citus--8.0-1--8.0-2.sql /usr/pgsql-13/share/extension/citus--8.0-1.sql /usr/pgsql-13/share/extension/citus--8.0-10--8.0-11.sql /usr/pgsql-13/share/extension/citus--8.0-11--8.0-12.sql /usr/pgsql-13/share/extension/citus--8.0-12--8.0-13.sql /usr/pgsql-13/share/extension/citus--8.0-13--8.1-1.sql /usr/pgsql-13/share/extension/citus--8.0-2--8.0-3.sql /usr/pgsql-13/share/extension/citus--8.0-3--8.0-4.sql /usr/pgsql-13/share/extension/citus--8.0-4--8.0-5.sql /usr/pgsql-13/share/extension/citus--8.0-5--8.0-6.sql /usr/pgsql-13/share/extension/citus--8.0-6--8.0-7.sql /usr/pgsql-13/share/extension/citus--8.0-7--8.0-8.sql /usr/pgsql-13/share/extension/citus--8.0-8--8.0-9.sql /usr/pgsql-13/share/extension/citus--8.0-9--8.0-10.sql /usr/pgsql-13/share/extension/citus--8.1-1--8.2-1.sql /usr/pgsql-13/share/extension/citus--8.2-1--8.2-2.sql /usr/pgsql-13/share/extension/citus--8.2-2--8.2-3.sql /usr/pgsql-13/share/extension/citus--8.2-3--8.2-4.sql /usr/pgsql-13/share/extension/citus--8.2-4--8.3-1.sql /usr/pgsql-13/share/extension/citus--8.3-1--9.0-1.sql /usr/pgsql-13/share/extension/citus--9.0-1--9.0-2.sql /usr/pgsql-13/share/extension/citus--9.0-2--9.1-1.sql /usr/pgsql-13/share/extension/citus--9.1-1--9.2-1.sql /usr/pgsql-13/share/extension/citus--9.2-1--9.2-2.sql /usr/pgsql-13/share/extension/citus--9.2-2--9.2-4.sql /usr/pgsql-13/share/extension/citus--9.2-4--9.3-2.sql /usr/pgsql-13/share/extension/citus--9.3-1--9.2-4.sql /usr/pgsql-13/share/extension/citus--9.3-2--9.4-1.sql /usr/pgsql-13/share/extension/citus--9.4-1--9.5-1.sql /usr/pgsql-13/share/extension/citus--9.5-1--10.0-1.sql /usr/pgsql-13/share/extension/citus.control /usr/share/doc/citus_13-10.0.3 /usr/share/doc/citus_13-10.0.3/CHANGELOG.md /usr/share/licenses/citus_13-10.0.3 /usr/share/licenses/citus_13-10.0.3/LICENSE
然后正常通过initdb创建postgresql数据库，1个CN，2个DN。
如下：
[zjh@lightdb1 pgsql-13]$ ll
total 24
drwxr-xr-x 2 zjh zjh 4096 Jun 1 17:43 bin
drwx------ 21 zjh zjh 4096 Aug 29 00:00 coordinator_1
drwxr-xr-x 3 zjh zjh 23 Jun 1 17:43 doc
drwxr-xr-x 3 zjh zjh 4096 Jun 19 14:58 lib
drwxr-xr-x 7 zjh zjh 4096 Jun 1 17:43 share
drwx------ 21 zjh zjh 4096 Aug 29 00:00 worker_1_13588
drwx------ 21 zjh zjh 4096 Aug 29 00:00 worker_2_23588
安装citus插件：
-- CN和DN都要配置 shared_preload_libraries=\'citus\' -- 第一个插件必须是citus CREATE EXTENSION citus; -- 安装在postgres用户下即可
SELECT * from citus_add_node(\'10.0.0.1\', 13588); SELECT * from citus_add_node(\'10.0.0.1\', 23588);
查询DN列表：
postgres=# SELECT * FROM citus_get_active_worker_nodes(); node_name | node_port --------------+----------- 10.0.0.1 | 23588 10.0.0.1 | 13588 (2 rows)
概念
在citus中，分片和节点不是一对一关系，这一点不同于greenplum，更接近nosql如couchbase的设计，一定程度上这么做也避免了使用了citus之后还需要分区的必要性（这是个优点、也是个缺点，平衡的结果）。
Citus表类型
citus中表分三种类型，1：分库表（每个DN n个分片，分片数量可配置，一般是订单表和客户表）；2：广播表（每个DN一份，CN不包括，一般是字典表、产品表、费率表、机构表、权限表等）；3：全局表（仅存在于CN，一些系统参数表，统计表，也可能广播存储，看情况），全局表一般不会和广播表、分库表进行关联，默认CN创建表的时候就是local表，也可以通过SELECT undistribute_table(\'github_events\');将分库表切换回local表（此时会数据先迁移回来，也是缩容的一种方式）。
广播表和分库表，广播表和广播表之间关联会很多。
同时会存在多种业务存在于同一个数据库中的情况，例如库存和客户，操作日志和订单，小二和菜单、功能、客户，并且同时有从菜单维度查，也有从小二维度查。所以citus支持对表进行分组，相关分组的表，citus在生成分布式执行计划的时候就知道那些是相关的，哪些是无关的。如下：
SELECT create_distributed_table(\'event\', \'tenant_id\');
SELECT create_distributed_table(\'page\', \'tenant_id\', colocate_with => \'event\');
分组的前提是两个表使用相同字段作为分片字段。分组可以使得SQL的优化更加进一步。
总有一会儿，你会发现库存和客户表进行关联，通过订单进行的。这个时候库存是根据产品分片的，客户是通过客户id分片的。此时效果会怎么样呢？
不同于greenplum支持distributed by语法，citus因为采用extension实现，没有扩展pg本身的语法，所以采用函数的方式来指定表是否为分布式表。
CREATE TABLE companies ( id bigserial PRIMARY KEY, name text NOT NULL, image_url text, created_at timestamp without time zone NOT NULL, updated_at timestamp without time zone NOT NULL ); SELECT create_distributed_table(\'companies\', \'id\'); -- companies表为分布式表，id是用于分片的字段
需要注意的是，citus分片数量和worker数量不是一一对应，这和gp不同，但类似于现在tidb、oceanbase的做法。如下：
要创建广播表，可以使用create_reference_table函数：
SELECT create_reference_table(\'geo_ips\'); -- 所有worker节点广播，不包含CN
大多数的DDL语句citus都支持，会负责分布式调用所有worker。
分布式数据库性能优化关键
co-location是分布式数据库性能好坏和扩展性的关键。
如果实在无法实现colocation，哪怕通过lightdb逻辑复制，尽可能避免下列操作：
1、agg(distinct value2)，带distinct的聚合函数
2、分析函数<window_function>() OVER (PARTITION BY <...> ORDER BY <...> <window_frame>)
3、任意字段排序和分页查询
3、对于这三种情况，gp的interconnect也无能为力，CN必然是瓶颈；
4、流式计算也不能解决to B端的问题，只能靠更加智能的算法和空间换时间；
自定义数据分布算法、副本数、分片数
Citus函数类型
不管用户是否承认，相同的功能，存储过程和函数实现的效率就是要比应用发送SQL过来效率更高。所以citus支持了分布式函数的概念。
新增节点
新增节点后，默认不会启用，需要调用rebalance_table_shards让citus对数据进行迁移，然后才会被访问。
SELECT rebalance_table_shards(\'companies\');
执行计划分析
explain(analyze,verbose,buffers) select count(*) as low_stock from ( select s_w_id, s_i_id, s_quantity from bmsql_stock where s_w_id = 975 and s_quantity < 12 and s_i_id in ( select ol_i_id from bmsql_district join bmsql_order_line on ol_w_id = d_w_id and ol_d_id = d_id and ol_o_id >= d_next_o_id - 20 and ol_o_id < d_next_o_id where d_w_id = 975 and d_id = 9 ) ) as L QUERY PLAN | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ Custom Scan (Citus Adaptive) (cost=0.00..0.00 rows=0 width=0) (actual time=9.781..9.782 rows=1 loops=1) | Output: remote_scan.low_stock | Task Count: 1 | Tuple data received from nodes: 1 bytes | Tasks Shown: All | -> Task | Query: SELECT count(*) AS low_stock FROM (SELECT bmsql_stock.s_w_id, bmsql_stock.s_i_id, bmsql_stock.s_quantity FROM public.bmsql_stock_103384 bmsql_stock WHERE ((bmsql_stock.s_w_id OPERATOR(pg_catalog.=) 975) AND (bmsql_stock.s_quantity OPERATOR(| Tuple data received from node: 1 bytes | Node: host=127.0.0.1 port=13588 dbname=postgres | -> Aggregate (cost=25597.32..25597.33 rows=1 width=8) (actual time=1.276..1.277 rows=1 loops=1) | Output: count(*) | Buffers: shared hit=810 | -> Nested Loop (cost=7612.59..25597.14 rows=73 width=0) (actual time=0.389..1.272 rows=4 loops=1) | Inner Unique: true | Buffers: shared hit=810 | -> HashAggregate (cost=7612.16..7646.24 rows=3408 width=4) (actual time=0.163..0.206 rows=186 loops=1) | Output: bmsql_order_line.ol_i_id | Group Key: bmsql_order_line.ol_i_id | Batches: 1 Memory Usage: 129kB | Buffers: shared hit=42 | -> Nested Loop (cost=0.71..7603.64 rows=3408 width=4) (actual time=0.055..0.131 rows=189 loops=1) | Output: bmsql_order_line.ol_i_id | Buffers: shared hit=42 | -> Index Scan using bmsql_district_pkey_103191 on public.bmsql_district_103191 bmsql_district (cost=0.27..8.30 rows=1 width=12) (actual time=0.014..0.014 rows=1 loops=1) | Output: bmsql_district.d_w_id, bmsql_district.d_id, bmsql_district.d_ytd, bmsql_district.d_tax, bmsql_district.d_next_o_id, bmsql_district.d_name, bmsql_district.d_street_1, bmsql_district.d_street_2, bmsql_district.d| Index Cond: ((bmsql_district.d_w_id = 975) AND (bmsql_district.d_id = 9)) | Buffers: shared hit=3 | -> Index Scan using bmsql_order_line_pkey_103351 on public.bmsql_order_line_103351 bmsql_order_line (cost=0.44..7561.26 rows=3408 width=16) (actual time=0.022..0.081 rows=189 loops=1) | Output: bmsql_order_line.ol_w_id, bmsql_order_line.ol_d_id, bmsql_order_line.ol_o_id, bmsql_order_line.ol_number, bmsql_order_line.ol_i_id, bmsql_order_line.ol_delivery_d, bmsql_order_line.ol_amount, bmsql_order_line.| Index Cond: ((bmsql_order_line.ol_w_id = 975) AND (bmsql_order_line.ol_d_id = 9) AND (bmsql_order_line.ol_o_id >= (bmsql_district.d_next_o_id - 20)) AND (bmsql_order_line.ol_o_id < bmsql_district.d_next_o_id)) | Buffers: shared hit=39 | -> Index Scan using bmsql_stock_pkey_103384 on public.bmsql_stock_103384 bmsql_stock (cost=0.43..5.27 rows=1 width=4) (actual time=0.006..0.006 rows=0 loops=186) | Output: bmsql_stock.s_w_id, bmsql_stock.s_i_id, bmsql_stock.s_quantity, bmsql_stock.s_ytd, bmsql_stock.s_order_cnt, bmsql_stock.s_remote_cnt, bmsql_stock.s_data, bmsql_stock.s_dist_01, bmsql_stock.s_dist_02, bmsql_stock.s_dist_03| Index Cond: ((bmsql_stock.s_w_id = 975) AND (bmsql_stock.s_i_id = bmsql_order_line.ol_i_id)) | Filter: (bmsql_stock.s_quantity < 12) | Rows Removed by Filter: 1 | Buffers: shared hit=768 | Planning Time: 0.755 ms | Execution Time: 1.498 ms | Planning: | Buffers: shared hit=3 | Planning Time: 0.324 ms | Execution Time: 9.796 ms |
一般SQL，失真不算很严重。
性能分析
高可用
流复制模式即可。
CN成为瓶颈
配置多个CN，前面架设一个LVS集群，但是CN不能动态扩展。
bypass-CN（direct-DN）模式
需要hash算法对外开放。
存储过程、函数与视图、序列、自增、标识列等特性
PostgreSQL SQL特性兼容性与限制
分非分布式事务和分布式事务。
使用benchmarksql进行TPC-C测试
因为TPC-C所有的表都co-location到warehouse_id了，所以跑TPCC是没有问题的。只不过citus的重写着实有点蠢。如下：
2021-10-07 21:21:47.037945T [239675] LOG: duration: 97782.322 ms execute <unnamed>: SELECT count(*) AS low_stock FROM (SELECT bmsql_stock.s_w_id, bmsql_stock.s_i_id, bmsql_stock.s_quantity FROM public.bmsql_stock_103379 bmsql_stock WHERE ((bmsql_stock.s_w_id OPERATOR(pg_catalog.=) $1) AND (bmsql_stock.s_quantity OPERATOR(pg_catalog.<) $2) AND (bmsql_stock.s_i_id OPERATOR(pg_catalog.=) ANY (SELECT bmsql_order_line.ol_i_id FROM (public.bmsql_district_103186 bmsql_district JOIN public.bmsql_order_line_103346 bmsql_order_line ON (((bmsql_order_line.ol_w_id OPERATOR(pg_catalog.=) bmsql_district.d_w_id) AND (bmsql_order_line.ol_d_id OPERATOR(pg_catalog.=) bmsql_district.d_id) AND (bmsql_order_line.ol_o_id OPERATOR(pg_catalog.>=) (bmsql_district.d_next_o_id OPERATOR(pg_catalog.-) 20)) AND (bmsql_order_line.ol_o_id OPERATOR(pg_catalog.<) bmsql_district.d_next_o_id)))) WHERE ((bmsql_district.d_w_id OPERATOR(pg_catalog.=) $3) AND (bmsql_district.d_id OPERATOR(pg_catalog.=) $4)))))) l 2021-10-07 21:21:47.037945T [239675] DETAIL: parameters: $1 = \'974\', $2 = \'13\', $3 = \'974\', $4 = \'10\'
同时，citus到worker节点后，执行计划的效果很不理想。有些select count(1)执行居然要几十秒，在单机时只要及时毫秒。tpmC从20万掉下到6万。
管理接口与管理工具
除了标准的建表功能外，分布式数据库至少要支持：
显示的广播接口，包括：到每个主worker节点，到每个主副worker节点，到每个主分片，到每个主副分片。
显示的单播可用接口，包括：到任一worker节点，到任一分片。
p14.6 Manual Query Propagation
查询数据分布情况
select * from pg_catalog.pg_dist_shard; -- 查询所有表的分片名 select * from pg_catalog.pg_dist_partition; -- 查询所有 select * from citus_tables ct; -- 所有citus管理的表
TPC-H测试
citus对TPC-H的支持不太好，准确的是说复杂关联支持不好。但凡涉及到关联字段不包含分片键、没有co-location的几乎都不支持。如下：
Vuser 1:Query Failed : select o_year, sum(case when nation = \'MOZAMBIQUE\' then volume else 0 end) / sum(volume) as mkt_share from ( select extract(year from o_orderdate) as o_year, l_extendedprice * (1 - l_discount) as volume, n2.n_name as nation from part, supplier, lineitem, orders, customer, nation n1, nation n2, region where p_partkey = l_partkey and s_suppkey = l_suppkey and l_orderkey = o_orderkey and o_custkey = c_custkey and c_nationkey = n1.n_nationkey and n1.n_regionkey = r_regionkey and r_name = \'AFRICA\' and s_nationkey = n2.n_nationkey and o_orderdate between date \'1995-01-01\' and date \'1996-12-31\' and p_type = \'STANDARD POLISHED STEEL\') all_nations group by o_year order by o_year : ERROR: complex joins are only supported when all distributed tables are co-located and joined on their distribution columns
Vuser 1:Query Failed : select cntrycode, count(*) as numcust, sum(c_acctbal) as totacctbal from ( select substr(c_phone, 1, 2) as cntrycode, c_acctbal from customer where substr(c_phone, 1, 2) in (\'23\', \'32\', \'17\', \'18\', \'16\', \'20\', \'25\') and c_acctbal > ( select avg(c_acctbal) from customer where c_acctbal > 0.00 and substr(c_phone, 1, 2) in (\'23\', \'32\', \'17\', \'18\', \'16\', \'20\', \'25\')) and not exists ( select * from orders where o_custkey = c_custkey)) custsale group by cntrycode order by cntrycode : ERROR: direct joins between distributed and local tables are not supported
因为citus是插件化，注定了不可能和原生GP一样默认为分布式MPP而生。开启citus.enable_repartition_joins后，有10个语句默认跑不通。
CITUS注意点
postgres=# create table t_batch(id int primary key generated always as identity,d1 bigint,d2 bigint,d3 bigint); CREATE TABLE postgres=# SELECT create_distributed_table(\'t_batch\',\'id\'); ERROR: cannot distribute relation: t_batch DETAIL: Distributed relations must not use GENERATED ... AS IDENTITY.
但是bigserial居然支持？
postgres=# create table t_batch(id bigserial primary key,d1 bigint,d2 bigint,d3 bigint); CREATE TABLE postgres=# SELECT create_distributed_table(\'t_batch\',\'id\'); create_distributed_table -------------------------- (1 row)
序列及序列作为默认值支持
postgres=# alter table bmsql_history postgres-# alter column hist_id set default nextval(\'bmsql_hist_id_seq\'); ALTER TABLE postgres=# alter table bmsql_history add primary key (hist_id); -- 约束必须加名字 ERROR: cannot create constraint without a name on a distributed table
alter table bmsql_history add constraint bmsql_history_pkey primary key (hist_id); ERROR: cannot create constraint on "bmsql_history" Detail: Distributed relations cannot have UNIQUE, EXCLUDE, or PRIMARY KEY constraints that do not include the partition column (with an equality operator if EXCLUDE).
postgres=# select pg_size_pretty(citus_relation_size(\'search_doc_new_ic\')); pg_size_pretty ---------------- 10045 MB (1 row) Time: 1.367 ms postgres=# select pg_size_pretty(citus_table_size(\'search_doc_new_ic\')); -- 不应该差这么多 pg_size_pretty ---------------- 216 GB (1 row) Time: 14.957 ms postgres=# select pg_size_pretty(citus_total_relation_size(\'search_doc_new_ic\')); pg_size_pretty ---------------- 243 GB (1 row)
主外键限制
tpch=# SELECT create_distributed_table(\'orders\', \'o_orderkey\'); NOTICE: Copying data from local table... NOTICE: copying the data has completed DETAIL: The local data in the table is no longer visible, but is still on disk. HINT: To remove the local data, run: SELECT truncate_local_data_after_distributing_table($$public.orders$$) ERROR: cannot create foreign key constraint since relations are not colocated or not referencing a reference table DETAIL: A distributed table can only have foreign keys if it is referencing another colocated hash distributed table or a reference table tpch=# \dS+ orders Table "public.orders" Column | Type | Collation | Nullable | Default | Storage | Stats target | Description -----------------+-----------------------------+-----------+----------+---------+----------+--------------+------------- o_orderdate | timestamp without time zone | | | | plain | | o_orderkey | numeric | | not null | | main | | o_custkey | numeric | | not null | | main | | o_orderpriority | character(15) | | | | extended | | o_shippriority | numeric | | | | main | | o_clerk | character(15) | | | | extended | | o_orderstatus | character(1) | | | | extended | | o_totalprice | numeric | | | | main | | o_comment | character varying(79) | | | | extended | | Indexes: "orders_pk" PRIMARY KEY, btree (o_orderkey) "order_customer_fkidx" btree (o_custkey) Foreign-key constraints: "order_customer_fk" FOREIGN KEY (o_custkey) REFERENCES customer(c_custkey) Referenced by: TABLE "lineitem" CONSTRAINT "lineitem_order_fk" FOREIGN KEY (l_orderkey) REFERENCES orders(o_orderkey) Access method: heap NOTICE: removing table public.lineitem from metadata as it is not connected to any reference tables via foreign keys tpch=# SELECT create_distributed_table(\'part\', \'p_partkey\'); NOTICE: Copying data from local table... NOTICE: copying the data has completed DETAIL: The local data in the table is no longer visible, but is still on disk. HINT: To remove the local data, run: SELECT truncate_local_data_after_distributing_table($$public.part$$) ERROR: cannot create foreign key constraint since foreign keys from reference tables and local tables to distributed tables are not supported DETAIL: Reference tables and local tables can only have foreign keys to reference tables and local tables
参数优化建议
citus参数调整建议： citus.shard_count=2*节点数 # 不建议太大，OLTP最大的表/16GB，OLAP系统最大的表/8GB，每个worker不能超过citus.max_adaptive_executor_pool_size。太多的话会导致广播查询时性能很差，因为每个分片都要去查询。
shard数量<=cpu数量（非超线程），因为citus是以shard而非worker为并发单位的。
# 主节点
findptdis=# insert into big_table select id, uuid() from generate_series(1,100000000) id
findptdis-# ;
INSERT 0 100000000
# 从节点
Tasks: 1539 total, 1 running, 1534 sleeping, 4 stopped, 0 zombie
%Cpu(s): 0.6 us, 0.2 sy, 0.0 ni, 99.1 id, 0.0 wa, 0.0 hi, 0.0 si, 0.0 st
KiB Mem : 39462998+total, 18012609+free, 25997252 used, 18850662+buff/cache
KiB Swap: 2097144 total, 2097144 free, 0 used. 32535580+avail Mem
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
92538 lightdb 20 0 66.2g 68288 62800 S 2.6 0.0 0:00.22 lightdb: lightdb findptdis 10.20.137.41(24542) COPY
92721 lightdb 20 0 66.2g 59784 54720 S 2.6 0.0 0:00.21 lightdb: lightdb findptdis 10.20.137.41(24920) COPY
92723 lightdb 20 0 66.2g 58908 53844 S 2.6 0.0 0:00.22 lightdb: lightdb findptdis 10.20.137.41(24932) COPY
92717 lightdb 20 0 66.2g 58760 53696 S 2.3 0.0 0:00.19 lightdb: lightdb findptdis 10.20.137.41(24884) COPY
92718 lightdb 20 0 66.2g 58072 53008 S 2.3 0.0 0:00.21 lightdb: lightdb findptdis 10.20.137.41(24896) COPY
92719 lightdb 20 0 66.2g 56568 51504 S 2.3 0.0 0:00.21 lightdb: lightdb findptdis 10.20.137.41(24908) COPY
92720 lightdb 20 0 66.2g 57468 52404 S 2.3 0.0 0:00.21 lightdb: lightdb findptdis 10.20.137.41(24916) COPY
92722 lightdb 20 0 66.2g 58900 53836 S 2.3 0.0 0:00.20 lightdb: lightdb findptdis 10.20.137.41(24926) COPY
92724 lightdb 20 0 66.2g 58956 53892 S 2.3 0.0 0:00.21 lightdb: lightdb findptdis 10.20.137.41(24934) COPY
92725 lightdb 20 0 66.2g 58396 53332 S 1.7 0.0 0:00.18 lightdb: lightdb findptdis 10.20.137.41(24936) COPY
219872 lightdb 20 0 66.2g 136436 132844 S 1.3 0.0 2:31.60 lightdb: walwriter
\timing可以测试citus和单机的延迟差距
citus.shard_max_size=32GB citus.log_distributed_deadlock_detection=true # 开发、测试环境 citus.local_table_join_policy=auto # 默认即可，如果需要，一般建议走参考表。除非表很大、写很不频繁、每次查询很小的数据，又很频繁（类似TA业务参数表、权限体系表，实际上又不是很合适） citus.binary_worker_copy_format
citus.coordinator_aggregation_strategy=\'disabled\'
citus.max_intermediate_result_size=-1
citus.all_modifications_commutative # 业务优化可用，一般会话级使用
citus.multi_task_query_log_level=log
citus.enable_repartition_joins=true
citus.enable_binary_protocol
citus.binary_worker_copy_format
citus.executor_slow_start_interval=5ms
citus.max_cached_conns_per_worker=2
citus.explain_all_tasks=true
citus.node_conninfo=\'sslmode=allow\'
主要的系统表
pg_dist_partition 存储分区表的元数据 pg_dist_colocation 每个表都有colocation pg_dist_shard 存储表分片的信息，包括hash键范围 citus_shards 上面三个表的组合视图 pg_dist_placement 分片某一副本所属worker的信息称为placement pg_dist_node 节点信息 citus.pg_dist_object 所有CN上创建的对象信息 citus_dist_stat_activity citus_worker_stat_activity citus_lock_waits pg_dist_authinfo pg_dist_poolinfo pg-dist-rebalance-strategy https://docs.citusdata.com/en/v10.2/develop/api_metadata.html#pg-dist-rebalance-strategy
主要的管理函数
citus_add_node citus_remove_node citus_get_active_worker_nodes master_get_table_metadata get_shard_id_for_distribution_column citus_relation_size citus_table_size citus_total_relation_size citus_move_shard_placement rebalance_table_shards The default strategy is appropriate under these circumstances: The shards are roughly the same size The shards get roughly the same amount of traffic Worker nodes are all the same size/type Shards haven’t been pinned to particular workers If any of these assumptions don’t hold, then the default rebalancing can result in a bad plan. In this case you may customize the strategy, using the rebalance_strategy parameter. It’s advisable to call get_rebalance_table_shards_plan before running rebalance_table_shards, to see and verify the actions to be performed. get_rebalance_table_shards_plan get_rebalance_progress citus_add_rebalance_strategy citus_set_default_rebalance_strategy citus_remote_connection_stats citus_drain_node
LightDB 22c计划增强
- 逻辑复制同步模式实现colocation
- 哈希算法外置实现direct copy
- 多字段分片，先机构id，再客户id；先客户id，再账户id，依赖于hash算法的二次开发
- 支持优化器提示
常见问题
DN节点
[lightdb@hs-10-20-30-195 log]$ grep 133029 lightdb-2022-01-09_052610.log 2022-01-09 05:41:43.628964T citus lightdb@findptlocaldis 10.20.137.41(50559) client backend ROLLBACK PREPARED 42704[2022-01-09 05:36:14 CST] 0 [221460] ERROR: prepared transaction with identifier "citus_0_133029_1096882410_5065" does not exist 2022-01-09 05:41:43.628964T citus lightdb@findptlocaldis 10.20.137.41(50559) client backend ROLLBACK PREPARED 42704[2022-01-09 05:36:14 CST] 0 [221460] STATEMENT: ROLLBACK PREPARED \'citus_0133029_1096882410_5065\'
CN节点
CN节点上也有分布式事务ID找不到的日志，但是日志级别是告警。
分析：两个可能性，1、没问题。因为2PC有一个失败的话，就会去回滚。所以CN是warning，DN是error。2、真的错了，citus 2PC实现有缺陷，citus误判。2pc日志本身保存在pg_dist_transaction中，理论上不会有pg_dist_transaction有，但是DN没有的情况（验证逻辑是需要分析和测试下有一个参与者失败的时候，发了几个回滚）。citus maintainer负责定期会去轮训清理。
DN节点 2022-01-15 11:38:26.049486T citus lightdb@findptlocaldis 192.168.1.113(51432) client backend ROLLBACK PREPARED 55000[2022-01-15 11:33:25 CST] 0 [22567] ERROR: prepared transaction with identifier "citus_0_53889_14465378_116756" is busy
DN节点
lightdb-2022-01-14_135814.log:2022-01-14 20:39:17.000449T citus lightdb@findptlocaldis 192.168.1.112(45070) client backend ROLLBACK PREPARED 0A000[2022-01-14 20:30:15 CST] 0 [21215] ERROR: prepared transaction belongs to another database lightdb-2022-01-14_135814.log-2022-01-14 20:39:17.000449T citus lightdb@findptlocaldis 192.168.1.112(45070) client backend ROLLBACK PREPARED 0A000[2022-01-14 20:30:15 CST] 0 [21215] HINT: Connect to the database where the transaction was prepared to finish it. lightdb-2022-01-14_135814.log-2022-01-14 20:39:17.000449T citus lightdb@findptlocaldis 192.168.1.112(45070) client backend ROLLBACK PREPARED 0A000[2022-01-14 20:30:15 CST] 0 [21215] STATEMENT: ROLLBACK PREPARED \'citus_0_14522_30628126_136054\'
CN节点报错
任何SQL都报错，如下：
配置shared_preload_libraries= \'citus,auto_explain,pg_stat_statements,pg_prewarm,pg_wait_sampling,pg_stat_kcache,pg_cron,pgaudit,pg_qualstats\'。跟auto_explain无关，不配置也发生空指针，methods为NULL。
citus与auto_explain冲突问题
https://github.com/citusdata/citus/issues/2920
https://github.com/citusdata/citus/pull/4068 说是9.5解决了，实际是我们是10.2.2，仍未解决。