Friday, February 15


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Performance limits of logical replication solutions

2ndQuadrant, pglogical, PostgreSQL, Tomas' PlanetPostgreSQL
In the previous blog post, I briefly explained how we got the performance numbers published in the pglogical announcement. In this blog post I’d like to discuss the performance limits of logical replication solutions in general, and also how they apply to pglogical. physical replication Firstly, let’s see how physical replication (built into PostgreSQL since version 9.0) works. A somewhat simplified figure of the with two just two nodes looks like this: Clients execute queries on the master node, the changes are written to a transaction log (WAL) and copied over network to WAL on the standby node. The recovery on the standby process on the standby then reads the changes from WAL and applies them to the data files just like during recovery. If the standby is in “hot_standby” (more…)

Performance of Sequences and Serials in Postgres-XL

2ndQuadrant, Pavan's PlanetPostgreSQL, PostgreSQL
In Postgres-XL, sequences are maintained at the Global Transaction Manager (GTM) to ensure that they are assigned non-conflicting values when they are incremented from multiple nodes. This adds significant overhead for a query doing thousands of INSERTs in a table with a serial column, incrementing sequence one at a time and making a network roundtrip to the GTM, for every INSERT. Shaun Thomas in a recent blog complained about INSERTs running a magnitude slower on Postgres-XL as compared to vanilla PostgreSQL. There is already a way to improve performance for sequences, but it’s clearly not well advertised. I thought this is a good opportunity to explain the facility. Postgres-XL provides a user-settable GUC called sequence_range. Every backend requests a block of sequence values as (more…)
Benchmarking Postgres-XL

Benchmarking Postgres-XL

2ndQuadrant, Featured, Pavan's PlanetPostgreSQL, PostgreSQL
As you may have noted from my previous blog, the last few months were busy in getting Postgres-XL up-to-date with the latest 9.5 release of PostgreSQL. Once we had a reasonably stable version of Postgres-XL 9.5, we shifted our attention to measure performance of this brand new version of Postgres-XL. Our choice of the benchmark is largely influenced by the ongoing work on the AXLE project, funded by the European Union under grant agreement 318633. Since we are using TPC BENCHMARK™ H to measure performance of all other work done under this project, we decided to use the same benchmark for evaluating Postgres-XL. It also suits Postgres-XL because TPC-H tries to measure OLAP workloads, something Postgres-XL should do well. 1. Postgres-XL Cluster Setup Once the benchmark was decided, (more…)

Working towards Postgres-XL 9.5

2ndQuadrant, Pavan's PlanetPostgreSQL, PostgreSQL
It’s been busy few months as we work towards merging Postgres-XL with the latest and greatest release of PostgreSQL. Postgres-XL is an open source fork of PostgreSQL that provides a scalable platform for OLTP and Business Intelligence. The current release of Postgres-XL is based on PostgreSQL 9.2, so it lacks all the improvements made to PostgreSQL over the last three years. 2ndQuadrant and other companies are working on bringing distributed scalability into PostgreSQL core as well as building tools and extensions outside the core. As part of that, Postgres-XL has a number of features that we’d like to bring back into core PostgreSQL, so 2ndQuadrant has picked up the task of updating the Postgres-XL code base to the latest PostgreSQL release as the first step. After more than 3 months (more…)