citusdata/cstore_fdw — 1.8k★ on GitHub (C). Columnar storage extension for Postgres built as a foreign data wrapper. Check out https://github.com/citusdata/citus for a modernized columnar storage implementation built as a table access method.
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Important notice: Columnar storage is now part of Citus
Columnar storage is now part of the Citus extension, which uses the table access method API to give a much more native experience. It also supports streaming replication, archival, rollback, and simplifies pg_upgrade. You can use Citus just for columnar storage on a single PostgreSQL server, or combine it with distributed tables to parallelize queries locally or across a cluster of PostgreSQL servers.
Migration is simple, and you'll typically see improved compression thanks to zstd:
-- After adding adding shared_preload_libraries = 'citus'
-- to postgresql.conf and restarting:
CREATE EXTENSION IF NOT EXISTS citus;
-- Create a table using the columnar access method, with the same columns
-- as an existing cstore_fdw table
CREATE TABLE customer_reviews_am (
LIKE customer_reviews_fdw INCLUDING ALL
) USING columnar;
-- Copy data from an old cstore_fdw table to an access method table
INSERT INTO customer_reviews_am SELECT * FROM customer_reviews_fdw;
-- cstore_fdw data size
SELECT pg_size_pretty(cstore_table_size('customer_reviews_fdw'));
┌────────────────┐
│ pg_size_pretty │
├────────────────┤
│ 100 MB │
└────────────────┘
-- Citus Columnar data size
SELECT pg_size_pretty(pg_table_size('customer_reviews_am'));
┌────────────────┐
│ pg_size_pretty │
├────────────────┤
│ 64 MB │
└────────────────┘
Read more about it in the Citus columnar blog post by Jeff Davis.
cstore_fdw
Cstore_fdw is an open source columnar store extension for PostgreSQL. Columnar stores provide notable benefits for analytics use cases where data is loaded in batches. Cstore_fdw’s columnar nature delivers performance by only reading relevant data from disk, and it may compress data 6x-10x to reduce space requirements for data archival.
Cstore_fdw is developed by Citus Data and can be used in combination with Citus, a postgres extension that intelligently distributes your data and queries across many nodes so your database can scale and your queries are fast. If you have any questions about how Citus can help you scale or how to use Citus in combination with cstore_fdw, please let us know.
Join the Mailing List to stay on top of the latest developments for Cstore_fdw.
Introduction
This extension uses a format for its data layout that is inspired by ORC,
the Optimized Row Columnar format. Like ORC, the cstore format improves
upon RCFile developed at Facebook, and brings the following benefits:
Compression: Reduces in-memory and on-disk data size by 2-4x. Can be extended
to support different codecs.
Column projections: Only reads column data relevant to the query. Improves
performance for I/O bound queries.
Skip indexes: Stores min/max statistics for row groups, and uses them to skip
over unrelated rows.
Further, we used the Postgres foreign data wrapper APIs and type representations
with this extension. This brings:
Support for 40+ Postgres data types. The user can also create new types and
use them.
Statistics collection. PostgreSQL's query optimizer uses these stats to
evaluate different query plans and pick the best one.
Simple setup. Create foreign table and copy data. Run SQL.
Building
cstore_fdw depends on protobuf-c for serializing and deserializing table metadata.
So we need to install these packages first:
# Fedora 17+, CentOS, and Amazon Linux
sudo yum install protobuf-c-devel
# Ubuntu 10.4+
sudo apt-get install protobuf-c-compiler
sudo apt-get install libprotobuf-c0-dev
# Ubuntu 18.4+
sudo apt-get install protobuf-c-compiler
sudo apt-get install libprotobuf-c-dev
# Mac OS X
brew install protobuf-c
Note. In CentOS 5, 6, and 7, you may need to install or update EPEL 5, 6, or 7 repositories.
See this page
for instructions.
Note. In Amazon Linux, the EPEL repository is installed by default, but not
enabled. See these instructions
for how to enable it.
Once you have protobuf-c installed on your machine, you are ready to build
cstore_fdw. For this, you need to include the pg_config directory path in
your make command. This path is typically the same as your PostgreSQL
installation's bin/ directory path. For example:
PATH=/usr/local/pgsql/bin/:$PATH make
sudo PATH=/usr/local/pgsql/bin/:$PATH make install
Note. cstore_fdw requires PostgreSQL version from 9.3 to 12. It doesn't
support earlier versions of PostgreSQL.
Usage
Before using cstore_fdw, you need to add it to shared_preload_libraries
in your postgresql.conf and restart Postgres:
The following parameters can be set on a cstore foreign table object.
filename (optional): The absolute path to the location for storing table data.
If you don't specify the filename option, cstore_fdw will automatically
choose the $PGDATA/cstore_fdw directory to store the files. If specified the
value of this parameter will be used as a prefix for all files created to
store table data. For example, the value /cstore_fdw/my_table could result in
the files /cstore_fdw/my_table and /cstore_fdw/my_table.footer being used
to manage table data.
compression (optional): The compression used for compressing value streams.
Valid options are none and pglz. The default is none.
stripe_row_count (optional): Number of rows per stripe. The default is
150000. Reducing this decreases the amount memory used for loading data
and querying, but also decreases the performance.
block_row_count (optional): Number of rows per column block. The default is
10000. cstore_fdw compresses, creates skip indexes, and reads from disk
at the block granularity. Increasing this value helps with compression and results
in fewer reads from disk. However, higher values also reduce the probability of
skipping over unrelated row blocks.
To load or append data into a cstore table, you have two options:
You can use the COPY command to load or append data from
a file, a program, or STDIN.
You can use the INSERT INTO cstore_table SELECT ... syntax to load or
append data from another table.
You can use the ANALYZE command to collect statistics
about the table. These statistics help the query planner to help determine the
most efficient execution plan for each query.
Note. We currently don't support updating table using DELETE, and UPDATE
commands. We also don't support single row inserts.
Updating from earlier versions to 1.7
To update an existing cstore_fdw installation from versions earlier than 1.6
you can take the following steps:
Download and install cstore_fdw version 1.6 using instructions from the "Building"
section,
Restart the PostgreSQL server,
Run ALTER EXTENSION cstore_fdw UPDATE;
Example
As an example, we demonstrate loading and querying data to/from a column store
table from scratch here. Let's start with downloading and decompressing the data
files.
Then, let's log into Postgres, and run the following commands to create a column
store foreign table:
-- load extension first time after install
CREATE EXTENSION cstore_fdw;
-- create server object
CREATE SERVER cstore_server FOREIGN DATA WRAPPER cstore_fdw;
-- create foreign table
CREATE FOREIGN TABLE customer_reviews
(
customer_id TEXT,
review_date DATE,
review_rating INTEGER,
review_votes INTEGER,
review_helpful_votes INTEGER,
product_id CHAR(10),
product_title TEXT,
product_sales_rank BIGINT,
product_group TEXT,
product_category TEXT,
product_subcategory TEXT,
similar_product_ids CHAR(10)[]
)
SERVER cstore_server
OPTIONS(compression 'pglz');
Next, we load data into the table:
\COPY customer_reviews FROM 'customer_reviews_1998.csv' WITH CSV;
\COPY customer_reviews FROM 'customer_reviews_1999.csv' WITH CSV;
Note. If you are getting ERROR: cannot copy to foreign table "customer_reviews" when trying to run the COPY commands, double check that you
have added cstore_fdw to shared_preload_libraries in postgresql.conf
and restarted Postgres.
Next, we collect data distribution statistics about the table. This is optional,
but usually very helpful:
ANALYZE customer_reviews;
Finally, let's run some example SQL queries on the column store table.
-- Find all reviews a particular customer made on the Dune series in 1998.
SELECT
customer_id, review_date, review_rating, product_id, product_title
FROM
customer_reviews
WHERE
customer_id ='A27T7HVDXA3K2A' AND
product_title LIKE '%Dune%' AND
review_date >= '1998-01-01' AND
review_date <= '1998-12-31';
-- Do we have a correlation between a book's title's length and its review ratings?
SELECT
width_bucket(length(product_title), 1, 50, 5) title_length_bucket,
round(avg(review_rating), 2) AS review_average,
count(*)
FROM
customer_reviews
WHERE
product_group = 'Book'
GROUP BY
title_length_bucket
ORDER BY
title_length_bucket;
Usage with Citus
The example above illustrated how to load data into a PostgreSQL database running
on a single host. However, sometimes your data is too large to analyze effectively
on a single host. Citus is a product built by Citus Data that allows you to run
a distributed PostgreSQL database to analyze your data using the power of multiple
hosts. You can easily install and run other PostgreSQL extensions and foreign data
wrappers—including cstore_fdw—alongside Citus.
You can create a cstore_fdw table and distribute it using the
create_distributed_table() UDF just like any other table. You can load data
using the copy command as you would do in single node PostgreSQL.
Using Skip Indexes
cstore_fdw partitions each column into multiple blocks. Skip indexes store minimum
and maximum values for each of these blocks. While scanning the table, if min/max
values of the block contradict the WHERE clause, then the block is completely
skipped. This way, the query processes less data and hence finishes faster.
To use skip indexes more efficiently, you should load the data after sorting it
on a column that is commonly used in the WHERE clause. This ensures that there is
a minimum overlap between blocks and the chance of them being skipped is higher.
In practice, the data generally has an inherent dimension (for example a time field)
on which it is naturally sorted. Usually, the queries also have a filter clause on
that column (for example you want to query only the last week's data), and hence you
don't need to sort the data in such cases.
Uninstalling cstore_fdw
Before uninstalling the extension, first you need to drop all the cstore tables:
postgres=# DROP FOREIGN TABLE cstore_table_1;
...
postgres=# DROP FOREIGN TABLE cstore_table_n;
Then, you should drop the cstore server and extension:
postgres=# DROP SERVER cstore_server;
postgres=# DROP EXTENSION cstore_fdw;
cstore_fdw automatically creates some directories inside the PostgreSQL's data
directory to store its files. To remove them, you can run:
$ rm -rf $PGDATA/cstore_fdw
Then, you should remove cstore_fdw from shared_preload_libraries in
your postgresql.conf:
Finally, to uninstall the extension you can run the following command in the
extension's source code directory. This will clean up all the files copied during
the installation:
$ sudo PATH=/usr/local/pgsql/bin/:$PATH make uninstall
Changeset
Version 1.7.0
(Fix) Add support for PostgreSQL 12
(Fix) Support count(t.*) from t type queries
(Fix) Build failures for MacOS 10.14+
(Fix) Make foreign scan parallel safe
(Fix) Add support for PostgreSQL 11 COPY
Version 1.6.2
(Fix) Add support for PostgreSQL 11
Version 1.6.1
(Fix) Fix crash during truncate (Cstore crashing server when enabled, not used)
(Fix) No such file or directory warning when attempting to drop database
Version 1.6
(Feature) Added support for PostgreSQL 10.
(Fix) Removed table files when a schema, extension or database is dropped.
(Fix) Removed unused code fragments.
(Fix) Fixed incorrect initialization of stripe buffers.
(Fix) Checked user access rights when executing truncate.
(Fix) Made copy command cancellable.
(Fix) Fixed namespace issue regarding drop table.
Version 1.5.1
(Fix) Verify cstore_fdw server on CREATE FOREIGN TABLE command
Version 1.5
(Feature) Added support for PostgreSQL 9.6.
(Fix) Removed table data when cstore_fdw table is indirectly dropped.
(Fix) Removed unused code fragments.
(Fix) Fixed column selection logic to return columns used in expressions.
(Fix) Prevented alter table command from changinf column type to incompatible types.
Version 1.4.1
(Fix) Compatibility fix for Citus copy command.
Version 1.4
(Feature) Added support for TRUNCATE TABLE
(Fix) Added support for PostgreSQL 9.5
Version 1.3
(Feature) Added support for ALTER TABLE ADD COLUMN and ALTER TABLE DROP COLUMN.
(Feature) Added column list support in COPY FROM.
(Optimization) Improve row count estimation, which results in better plans.
(Fix) Fix the deadlock issue during concurrent inserts.
(Fix) Return correct result when using whole row references.
Version 1.2
(Feature) Added support for COPY TO.
(Feature) Added support for INSERT INTO cstore_table SELECT ....
(Optimization) Improved memory usage.
(Fix) Dropping multiple cstore tables in a single command cleans-up files
of all them.
Version 1.1
(Feature) Make filename option optional, and use a default directory inside
$PGDATA to manage cstore tables.
(Feature) Automatically delete files on DROP FOREIGN TABLE.
(Fix) Return empty table if no data has been loaded. Previously, cstore_fdw
errored out.
(Fix) Fix overestimating relation column counts when planning.
(Feature) Added cstore_table_size(tablename) for getting the size of a cstore
table in bytes.
Copyright
Copyright (c) Citus Data, Inc.
This module is free software; you can redistribute it and/or modify it under the
Apache v2.0 License.
For all types of questions and comments about the wrapper, please contact us at
engage @ citusdata.com.
How active is development on citusdata/cstore_fdw?
The most recent commit recorded on citusdata/cstore_fdw was 5.5 years ago, based on the GitHub push timestamp. The repository has 169 forks — one of the better signals of community interest.
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What else is in the Data space?
citusdata/cstore_fdw is tracked by TopGit under the Data category, alongside 4 GitHub-tagged topics. Trending and Topics pages list peer repositories of comparable stars and language.
What language is citusdata/cstore_fdw written in?
citusdata/cstore_fdw is written primarily in C. GitHub's language field is based on the largest share of bytes in the default branch.
What topics is citusdata/cstore_fdw associated with?
GitHub's repository topics for citusdata/cstore_fdw: "columnar-storage", "columnar-store", "compression", "postgresql". TopGit's editorial category is Data.
Where do I read more about citusdata/cstore_fdw?
This TopGit page is a snapshot — the READ ME tab shows the project's own README content (links stripped, images preserved). The GitHub repository at github.com/citusdata/cstore_fdw is the definitive source.
Why is citusdata/cstore_fdw categorized under Data?
TopGit places citusdata/cstore_fdw in the Data category based on its GitHub topics and description (tagged: "columnar-storage", "columnar-store", "compression"). Categories are assigned from real repository metadata, not editorial guesswork.
Read full README in the tab above.
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