Regional Tables

In a multi-region deployment, the Regional Table Locality Pattern is a good choice for tables with the following requirements:

  • Read and write latency must be low.
  • Rows in the table, and all latency-sensitive queries, can be tied to specific regions.
Note:

Tables with the Regional Table Locality Pattern can survive zone or region failures, depending on the database-level survival goal setting.

Note:

Regional tables (and the other multi-region capabilities) require an Enterprise license.

Prerequisites

Fundamentals

Multi-region patterns require thinking about the following questions:

For more information about our multi-region capabilities, review the following pages:

In addition, reviewing the following information will be helpful:

Cluster setup

Each multi-region pattern assumes the following setup:

Multi-region hardware setup

Hardware

  • 3 regions
  • Per region, 3+ AZs with 3+ VMs evenly distributed across them
  • Region-specific app instances and load balancers
    • Each load balancer redirects to CockroachDB nodes in its region.
    • When CockroachDB nodes are unavailable in a region, the load balancer redirects to nodes in other regions.

Cluster

Each node is started with the --locality flag specifying its region and AZ combination. For example, the following command starts a node in the west1 AZ of the us-west region:

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$ cockroach start \
--locality=region=us-west,zone=west1 \
--certs-dir=certs \
--advertise-addr=<node1 internal address> \
--join=<node1 internal address>:26257,<node2 internal address>:26257,<node3 internal address>:26257 \
--cache=.25 \
--max-sql-memory=.25 \
--background

Configuration

Summary

To use this pattern, you tell CockroachDB to set the table locality to either REGIONAL BY TABLE or REGIONAL BY ROW.

Regional tables

Regional tables work well when your application requires low-latency reads and writes for an entire table from a single region.

For regional tables, access to the table will be fast in the table's "home region" and slower in other regions. In other words, CockroachDB optimizes access to data in regional tables from a single region. By default, a regional table's home region is the database's primary region, but that can be changed to use any region in the database.

For instructions showing how to set a table's locality to REGIONAL BY TABLE, see ALTER TABLE ... SET LOCALITY

Note:

By default, all tables in a multi-region database are regional tables that use the database's primary region. Unless you know your application needs different performance characteristics than regional tables provide, there is no need to change this setting.

Regional by row tables

In regional by row tables, individual rows are optimized for access from different regions. This setting automatically divides a table and all of its indexes into partitions, with each partition optimized for access from a different region. Like regional tables, regional by row tables are optimized for access from a single region. However, that region is specified at the row level instead of applying to the whole table.

Use regional by row tables when your application requires low-latency reads and writes at a row level where individual rows are primarily accessed from a single region. For example, a users table in a global application may need to keep some users' data in specific regions for better performance.

For an example of a table that can benefit from the regional by row setting in a multi-region deployment, see the users table from the MovR application.

For instructions showing how to set a table's locality to REGIONAL BY ROW, see ALTER TABLE ... SET LOCALITY

Steps

Note:

By default, all tables in a multi-region database are Regional tables. Therefore, the steps below show how to set up Regional by row tables.

First, create a database and set it as the default database:

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CREATE DATABASE test;
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USE test;

This cluster is already deployed across three regions. Therefore, to make this database a "multi-region database", you need to issue the following SQL statement that sets the primary region:

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ALTER DATABASE test PRIMARY REGION "us-east";
Note:

Every multi-region database must have a primary region. For more information, see Database regions.

Next, issue the following ADD REGION statements to add the remaining regions to the database.

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ALTER DATABASE test ADD REGION "us-west";
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ALTER DATABASE test ADD REGION "us-central";

Congratulations, test is now a multi-region database!

Next, create a users table:

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CREATE TABLE users (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    city STRING NOT NULL,
    first_name STRING NOT NULL,
    last_name STRING NOT NULL,
    address STRING NOT NULL
);

By default, all tables in a multi-region cluster default to the REGIONAL BY TABLE locality setting. To verify this, issue a SHOW CREATE on the users table you just created:

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SHOW CREATE TABLE users;
  table_name |                        create_statement
-------------+------------------------------------------------------------------
  users      | CREATE TABLE public.users (
             |     id UUID NOT NULL DEFAULT gen_random_uuid(),
             |     city STRING NOT NULL,
             |     first_name STRING NOT NULL,
             |     last_name STRING NOT NULL,
             |     address STRING NOT NULL,
             |     CONSTRAINT "primary" PRIMARY KEY (id ASC),
             |     FAMILY "primary" (id, city, first_name, last_name, address)
             | ) LOCALITY REGIONAL BY TABLE IN PRIMARY REGION

Next, set the table's locality to REGIONAL BY ROW using the ALTER TABLE ... SET LOCALITY statement:

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ALTER TABLE users SET LOCALITY REGIONAL BY ROW;
NOTICE: LOCALITY changes will be finalized asynchronously; further schema changes on this table may be restricted until the job completes
ALTER TABLE SET LOCALITY

Now that the table is regional by row, we need to tell CockroachDB which rows need to be optimized for access from which regions. We do this by issuing UPDATE statements that modify the automatically created crdb_region column.

Issue the statements below to associate each row with a home region that depends on its city column:

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UPDATE users SET crdb_region = 'us-central'   WHERE city IN ('chicago', 'milwaukee', 'dallas');
UPDATE users SET crdb_region = 'us-east'      WHERE city IN ('washington dc', 'boston', 'new york');
UPDATE users SET crdb_region = 'us-west'      WHERE city IN ('los angeles', 'san francisco', 'seattle');

By default, the region column will get auto-assigned on insert; this is also known as "auto-homing". For more information about how the crdb_region column works, see ALTER TABLE ... SET LOCALITY REGIONAL BY ROW.

Note that there is a performance benefit for queries that select a single row (e.g., SELECT * FROM users WHERE email = 'anemailaddress@gmail.com'). If 'anemailaddress@gmail.com' is found in the local region, there is no need to search remote regions. This feature, whereby the SQL engine will avoid sending requests to nodes in other regions when it can read a value from a unique column that is stored locally, is known as locality optimized search.

Tip:

A good way to check that your table locality settings are having the expected effect is by monitoring how the performance metrics of a workload change as the settings are applied to a running cluster. For a tutorial showing how table localities can improve performance metrics across a multi-region cluster, see Low Latency Reads and Writes in a Multi-Region Cluster.

Characteristics

Latency

For REGIONAL BY TABLE tables, you get low latency for single-region writes and reads, as well as multi-region stale reads.

For REGIONAL BY ROW tables, you get low-latency consistent multi-region reads & writes for rows which are homed in specific regions, and low-latency multi-region stale reads from all other regions.

Resiliency

Because the test database does not specify a survival goal, it uses the default ZONE survival goal. With the default settings, an entire availability zone (AZ) can fail without interrupting access to the database.

For more information about how to choose a database survival goal, see When to use ZONE vs. REGION survival goals.

Alternatives

  • If rows in the table cannot be tied to specific geographies, reads must be up-to-date for business reasons or because the table is referenced by foreign keys, and the table is rarely modified, consider the GLOBAL Table Locality Pattern.
  • If your application can tolerate historical reads in some cases, consider the Follower Reads pattern.

Tutorial

For a step-by-step demonstration showing how CockroachDB's multi-region capabilities (including REGIONAL BY ROW tables) give you low-latency reads in a distributed cluster, see the tutorial on Low Latency Reads and Writes in a Multi-Region Cluster.

See also

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