![]() You can use the regular expression module ( re) to match words and patterns in the query string, or use the SQL parser module ( sqlparse) to support more sophisticated/robust query parsing. Your routing function has access to the full power of the Python language and the myriad of available Python modules. The logic can be as simple or as sophisticated as you want. Your routing function can choose a server for each query based on any combination of the client username, the query string, random variables, or external input. Here’s another example: you might want to implement controlled load balancing (or A/B testing) across replicated clusters or servers. And, of course, any query must run entirely on the server to which is it routed cross-database joins or multi-server transactions do not work! In fact, you can even mix and match Amazon Redshift and PostgreSQL, taking care to ensure that your Python functions correctly handle any server-specific grammar in your queries your database will throw errors if your routing function sends queries it can’t process. This can be extended to support multiple Amazon Redshift clusters or PostgreSQL instances. You can determine the appropriate cluster for any given query based on the names of the schemas or tables used in the query. How it does this is entirely up to you.įor example, you might want to run two Amazon Redshift clusters, each optimized to host a distinct data warehouse subject area. Its return value must identify the target database server. Your function is called for each query, with the client username and the query string as parameters. The routing feature maps client connections to server connections using a Python routing function which you provide. Now I’d like to talk about the query routing and query rewrite feature enhancements. You can choose to run it as a bastion server using SSH tunneling, or you can use pgbouncer’s recently introduced SSL support for encryption and authentication.ĭocumentation and community support for pgbouncer can be easily found online pgbouncer-rr is a superset of pgbouncer. It can be deployed to a public subnet while your servers reside in private subnets. It can live in an Auto Scaling group, and behind an Elastic Load Balancing load balancer. You can deploy multiple instances of pgbouncer-rr to avoid throughput bottlenecks or single points of failure, or to support multiple configurations. Any target application can be connected to pgbouncer-rr as if it were an Amazon Redshift or PostgreSQL server, and pgbouncer-rr creates a connection to the actual server, or reuses an existing connection. Pgbouncer-rr works the same way as pgbouncer. Rewrite: Intercept and programmatically change client queries before they are sent to the server use it to optimize or otherwise alter queries without modifying your application.Routing: Intelligently send queries to different database servers from one client connection use it to partition or load balance across multiple servers or clusters. ![]() The pgbouncer-rr project is based on pgbouncer, an open source, PostgreSQL connection pooler. Have you ever wanted to split your database load across multiple servers or clusters without impacting the configuration or code of your client applications? Or perhaps you have wished for a way to intercept and modify application queries, so that you can make them use optimized tables (sorted, pre-joined, pre-aggregated, etc.), add security filters, or hide changes you have made in the schema? For more information, please review the Amazon Redshift documentation article, “ Querying Data with Federated Query in Amazon Redshift.” ![]() ![]() NOTE: You can now use federated queries in Amazon Redshift to query and analyze data across operational databases, data warehouses, and data lakes. This post was last reviewed and updated August, 2022 with a section on Deploying pgbouncer in Elastic Kubernetes Service (EKS). ![]() If you're looking to use PostgREST however, they do have an official Docker image that you can use over here. Unfortunately, I can't really recommend you which one since there doesn't seem to be an official Docker image for PgBouncer and I myself have never tried any of the existing ones out there. You can still connect the DB with a PgBouncer image spun up in another container however. We've since updated our README to make that clearer :-) All the other features such as this and this are only available in the AWS EC2 or DO droplet images. Just to clarify, our Docker image only contains the latest version of Postgres (13) and the common extensions listed out here. Hi! I'm one of the contributors to the repo. ![]()
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