![]() This is the rebased and updated patch, it was reviewed by several community members and updated patches were submitted to hackers. Masahiko Swada recently added the patch to the commit fest, the commit fest entry is given below… There has been number of back and forth on this feature and so far the design is not blessed by the senior members of the community. ![]() The patch for supporting two phase commit for FDW transactions was submitted to the community few years back. This feature is required in order to support OLTP workload hence it is very important for sharding feature. This feature is required in order to guarantee data consistency across the database cluster. I am providing the latest updates on these features and some rough guesses on when we can see these in PG however it is never easy to predict when a feature will get committed to PostgreSQL.ġ- Global transaction manager (Two Phase commit for FDW transactions)Ĭurrently FDW transactions don’t support two phase commit, this means that if you are using multiple foreign servers in a transaction and if one part of transaction fails in one foreign server then the entire transaction on all foreign serves are suppose to fail. Again I talked about these features in my earlier blogs however the balls has moved forward slightly on these since my blogs from August 2019. This section talks about the missing features that are required to achieve the MVP for sharding in PostgreSQL. The following partition is created on the shard : The partition is created on the primary node : The parent table is created on the primary node : The short example describe how a sharded table can be created today using the postgres_fdw.įollowing commands are executed on the primary node, the foreign server is creating pointing to the database shard, the user mapping for the shard is created accordingly. My series of blogs mentioned in the introduction discusses the FDW sharding feature and its architecture in detail, only mentioning the summary here for the context. The trade-off with FDW sharding is that it is using a trusted architecture and it is more simpler and relatively less time consuming to implements as compared to other methods… Using the FDW architecture surely adds some overhead which can be avoided by other more sophisticated cross node communication techniques. Please note that FDW based sharding the approach that PostgreSQL community is following in order to implement this feature. This enables the heavy query processing to be done on the shards and only results of the query are sent back to the primary node. Using the FDW based sharding, the data is partitioned to the shards, in order to optimise the query for the sharded table, various parts of the query i.e aggregates, join etc are pushed down to the shards. PostgreSQL provides number of foreign data wrapper (FDW’s) that are used for accessing external data sources, the postgres_fdw is used for accessing Postgres database running on external server i.e. The build-in sharding feature in PostgreSQL is using the FDW based approach, the FDW’s are based on sql/med specification that defines how an external data source can be accessed from the PostgreSQL server. Sharding allows the table to be partitioned in a way that the partitions live on external foreign servers and the parent table lives on the primary node where the user is creating the distributed table. While declarative partitioning feature allows the user to partition the table into multiple partitioned tables living on the same database server. It is the mechanism to partition a table across one or more foreign servers. ![]() Just to recap, sharding in database is the ability to horizontally partition the data across one more database shards. Last but not the least the blog will continue to emphasise the importance of this feature in the core of PostgreSQL. The blog also mentions some features that are far fetched and potentially not needed for MVP however they are really important for enterprise level deployment of a distributed cluster solution. Little has happened since then, the purpose of this blog is discuss the important missing pieces of the puzzle, what are the minimum set of features needed to get to MVP (minimum viable product) and most importantly which efforts are currently going on to get to the MVP of Sharding in PostgreSQL core. Back in August 2019, I wrote multiple blogs with the title of “Horizontal scalability with Sharding in PostgreSQL – Where it is going Part 1.
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