Creating a Columnstore Table

The default table type in SingleStoreDB is columnstore. The default can be changed to rowstore by updating the default_table_type engine variable to rowstore. See List of Engine Variables for more details.

Currently, SingleStoreDB supports one sort key per table; however, if you do not want to define a key (e.g. if records are already inserted in the right order or you do not care about the sort order), SORT KEY().

Note

KEY() USING CLUSTERED COLUMNSTORE is a legacy syntax that is equivalent to SORT KEY(). We recommend using SORT KEY().

Here is an example of a query that creates a columnstore table:

CREATE TABLE products (
ProductId INT,
Color VARCHAR(10),
Price INT,
Qty INT,
SORT KEY (Price),
SHARD KEY (ProductId)
);

As with any other SingleStoreDB table, we define a SHARD KEY to explicitly control the data distribution. We define it on ProductId since sharding on a high cardinality identifier column generally allows for a more even distribution and prevents skew. It is also possible to randomly distribute data by either omitting the shard key, or defining an empty shard key SHARD KEY(). You can have at most one shard key that is defined on zero or more columns.

Your columnstore table definition can contain metadata-only unenforced unique keys, single-column hash keys (which may be UNIQUE), and a FULLTEXT key. You cannot define more than one unique key.

For more information on creating columnstore tables that use hash keys, see USING HASH behavior.

Besides the keys discussed so far in this section, you cannot add other keys to a columnstore table.

If a sort key is defined on a table, the rows of that table will be stored in a highly compressed columnar format on disk. Storage is optimized for efficient scan in the key order. Use of an empty key in the form of SORT KEY() is permitted and results in less expensive background maintenance of the columnstore table, without guaranteeing any particular order.

We describe the details of the format below. While SingleStoreDB can execute any query on a columnstore table that it can execute on a rowstore, some queries are more suitable for columnstore tables than others. Some queries that can benefit from using columnstore include:

  • Queries that scan several columns out of a table with many columns. Columnstore table will only materialize columns that it actually needs to perform the query.

  • Queries that scan a lot of data in sort key order. Scans in the columnstore key order are more CPU and memory efficient.

  • Joins between two columnstore tables on the sort key. Such a join can be executed as a merge join, resulting in a good performance and low memory overhead.

  • Queries with high selectivity filters on the sort key. By leveraging a technique called segment elimination, SingleStoreDB can open only those row segments that actually contain relevant rows, significantly improving the performance of queries with high selectivity.

Columnstore tables are also not constrained by the amount of available memory, unlike rowstore tables.

Creating a Columnstore Table Using Standard CREATE TABLE Syntax

The columnstore as default feature allows you to create a columnstore table using standard CREATE TABLE syntax.

The Benefit of Using the Columnstore for Transaction Processing

Although rowstores are well-suited for transaction processing, it can be costly to store large datasets in rowstores, as they store all data in RAM. Because columnstores are disk-based, it is more economical to store data in columnstores as opposed to rowstores.

The columnstore continues to evolve to support transactional workloads that would have traditionally used the rowstore. At the same time, the columnstore provides the fastest query processing performance for analytical workloads, making it a good choice for a mix of both transactional and analytical requirements.

Enabling Columnstore as Default

The default_table_type engine variable specifies whether CREATE TABLE creates a rowstore or columnstore table, by default.

Note

default_table_type is set to rowstore by default.

In SingleStoreDB, to change default_table_type to columnstore, set the variable:

SET GLOBAL default_table_type = 'columnstore';

You can create a rowstore table with CREATE ROWSTORE TABLE ..., regardless of the setting of default_table_type.

Conversion of Standard CREATE TABLE Syntax to Columnstore CREATE TABLE Syntax

When the default_table_typecolumnstore, the query engine internally converts standard CREATE TABLE syntax to equivalent columnstore-specific CREATE TABLE syntax, as follows:

SORT KEY()

The SORT KEY() clause is added, if you have not specified the clause explicitly. For example,

CREATE TABLE t(a INT, b INT);

is equivalent to:

CREATE TABLE t(a INT, b INT, SORT KEY());

KEY(...)

Single-Column Keys

KEY(<column name>) is equivalent to KEY(<column name>) USING HASH. For example,

CREATE TABLE t(a INT, b INT, KEY(a));

is equivalent to:

CREATE TABLE t(a INT, b INT, SORT KEY(), KEY(a) USING HASH);
Multi-Column Keys

KEY(<column 1 name>,<column 2 name>,... <column n name> is equivalent to KEY(<column 1 name>) USING HASH, KEY(<column 2 name>) USING HASH, KEY(<column n name>) USING HASH.

CREATE TABLE t(a INT, b INT, c INT, KEY(a,b));

is equivalent to:

CREATE TABLE t(a INT, b INT, SORT KEY(), KEY(a) USING HASH, KEY(b) USING HASH);

Using multi-column unique keys in a columnstore table is supported starting in engine version 7.5.

A query against t with an equality filter on a, an equality filter on b, or equality filters on both a and b could benefit from KEY(a,b) USING HASH. A query that uses both equality filters would be the most efficient.

Unlike other database products, SingleStoreDB utilizes per-segment inverted indexes and cross-segment indexes to support multi-column keys while minimizing storage costs.

Each secondary index contains a collection of multiple cross-segment indexes, each of which is a hash table covering one or more segments. The background merger works to merge the hash tables to reduce the number of lookups necessary for a seek operation.

These data structures work together to accomplish these fast seeks as follows:

  • The inverted index is built to map values of an index column to a posting list that stores row offsets within the segment with the value searched. The posting list logs which segment a specific value is located and uses row offsets to determine the value is located.

  • The cross-segment indexes map values of each indexed column with the ID of the segment where the searched value is located. The cross-segment indexes also map to the starting location of the corresponding postings list in the inverted index for each segment. Lastly, for a multi-column index like the example above (KEY(a,b) USING HASH)), another collection of cross-segment indexes are built on the row of indexed columns to map from the hash of each tuple (value_a and value_b) to the starting locations of the corresponding per-segment postings lists for value_a and value_b.

UNIQUE KEY

UNIQUE KEY(<column name>) is created as UNIQUE KEY(<column name>) USING HASH. For example,

CREATE TABLE t(a INT, b INT, SHARD(a), UNIQUE KEY(a));

is equivalent to:

CREATE TABLE t(a INT, b INT, SORT KEY(), SHARD(a), UNIQUE KEY(a) USING HASH);

Note

The use of multiple unique keys is not supported in columnstore tables. A unique key must contain one of the columns of the shard key. The shard key cannot be empty in this case and can contain multiple columns.

PRIMARY KEY

PRIMARY KEY(<column name>) is created as SHARD(<column name>), UNIQUE KEY(<column name>) USING HASH.

For example, CREATE TABLE t(a INT PRIMARY KEY, b INT); or CREATE TABLE t(a INT, b INT, PRIMARY KEY(a)); is equivalent to:

CREATE TABLE t(a INT NOT NULL, b INT, SORT KEY(), SHARD(a), UNIQUE KEY `PRIMARY` (a) USING HASH);

Considerations When Using Hash Keys and Sort Keys

Warning

The previous section explained that in columnstore as default mode, a standard CREATE TABLE statement using KEY(<k>) stores <k> as a hash key in the resulting columnstore table. Hash keys support fast equality lookups, but not fast range filters. If you want to use a range filter on a columnstore, you need to use a sort key <sk> by explicitly specifying SORT KEY(<sk>) in your CREATE TABLE statement.

Viewing the Storage Structure of a Table

Note

After creating a columnstore table using standard CREATE TABLE syntax, run SHOW CREATE TABLE if you wish to see the table’s full, explicit definition of keys and sharding.

Converting an Existing Rowstore Table to a Columnstore Table

You can convert an existing rowstore table to a columnstore table by creating a new columnstore table, copying the data from the rowstore table to the columnstore table, dropping the rowstore table, and renaming the columnstore table to the rowstore table. For example, suppose you have an existing rowstore table t with the columns a INT and b INT. You can convert this table to a columnstore table as follows, assuming default_table_type is set to columnstore:

CREATE TABLE t2(a INT, b INT) AS SELECT * FROM t;
DROP TABLE t;
ALTER TABLE t2 RENAME TO t;

Example Database Schema that is Created with Columnstore as Default

Suppose you want to create a database schema track_visits that tracks page visits on a website. For each page (URL) that is visited, you store the host name and path of the URL. For example, for the URL myexample.com/a/b/, the host name is myexample.com and the path is a/b.

For each page that is visited, you store the date/time of the visit and the user who visited the page. You also store the account that each user belongs to.

The schema contains the tables accounts, users, webpages and webpage_visits. The definitions for these tables are provided in the Standard Syntax for Creating the Tables in the Schema section.

Use Case for Using Default as Columnstore to Create the track_visits Schema

Analytical Processing

Columnstores (as compared to rowstores) are optimized for analytical processing. With this schema, you can more quickly answer analytical questions such as:

  • How many visits occurred within a particular time period?

  • On average, how many visits are there per user?

  • On average, how many users are there per account?

  • How many unique webpages were clicked?

Transactional Processing

You can utilize the Universal Storage capabilities to perform transaction processing operations on the tables in the schema. For example:

  • To find all of the webpage visits containing a particular hostname, you can run a query such as SELECT * FROM webpages WHERE url_host = 'myexample.com';. This query allows you take advantage of the hash index on url_host, which allows the query to run faster than if the hash index was not used.

  • To find all of the webpages visited on a particular date and time, you can run a query such as SELECT * FROM webpage_visits v JOIN webpages w ON v.page_id = w.id WHERE v.when_clicked = '2020-01-01 16:35:00'; This query does a highly selective join, as there are only a few records in webpage_visits that match the equality filter on when_clicked.

Standard CREATE TABLE Syntax for Creating the Tables in the track_visits Schema

Following are the CREATE TABLE statements for the tables in the track_visits schema. The statements use standard CREATE TABLE syntax. The statements are run in columnstore as default mode.

CREATE DATABASE track_visits;
USE track_visits;
CREATE REFERENCE TABLE accounts(
id INT AUTO_INCREMENT,
name TEXT,
PRIMARY KEY(id),
UNIQUE KEY(name)
);
CREATE TABLE users (
id BIGINT AUTO_INCREMENT,
user_name TEXT,
account_id BIGINT,
PRIMARY KEY (id)
);
CREATE TABLE webpages(
id BIGINT AUTO_INCREMENT,
url_host TEXT,
url_path TEXT,
PRIMARY KEY (id),
KEY(url_host)
);
CREATE TABLE webpage_visits(
id BIGINT AUTO_INCREMENT,
user_id BIGINT,
page_id INT,
when_clicked DATETIME,
PRIMARY KEY (id),
KEY (user_id, page_id),
KEY (when_clicked)
);

Storage Structure of Tables in the track_visits Schema

The following definitions show the structure of the tables in the track_visits schema after they are stored as a result of running the standard CREATE TABLE statements.

Note

INT, and BIGINT, which are used in the standard CREATE TABLE statements, are stored as INT(11) and BIGINT(20), respectively.

In some cases, TEXT is stored as BLOB (they are equivalent).

This behavior is independent of the columnstore as default feature.

accounts
CREATE REFERENCE TABLE accounts(
id INT NOT NULL AUTO_INCREMENT,
name TEXT,
UNIQUE KEY `PRIMARY` (id) USING HASH,
UNIQUE KEY(name) USING HASH,
SORT KEY()
);
users
CREATE TABLE users (
id BIGINT(20) NOT NULL AUTO_INCREMENT,
user_name TEXT,
account_id BIGINT,
SHARD(id),
UNIQUE KEY `PRIMARY` (id) USING HASH,
SORT KEY()
);
webpages
CREATE TABLE webpages(
id BIGINT NOT NULL AUTO_INCREMENT,
url_host BLOB,
url_path BLOB,
SHARD(id),
UNIQUE KEY `PRIMARY` (id) USING HASH,
KEY(url_host) USING HASH,
SORT KEY()
);
webpage_visits
CREATE TABLE webpage_visits(
id BIGINT(20) NOT NULL AUTO_INCREMENT,
user_id BIGINT(20),
page_id INT(11),
when_clicked DATETIME,
SHARD(id),
UNIQUE KEY `PRIMARY` (id) USING HASH,
KEY(user_id) USING HASH,
KEY(page_id) USING HASH,
KEY (when_clicked) USING HASH,
SORT KEY()
);
Querying webpage_visits Using a Range Filter

If you intend to query webpage_visits using a range filter on when_clicked, you could have made when_clicked the sort key. You could have done this using the following standard CREATE TABLE syntax.

CREATE TABLE webpage_visits(
id BIGINT AUTO_INCREMENT,
user_id BIGINT,
page_id INT,
when_clicked DATETIME,
PRIMARY KEY (id),
KEY (user_id, page_id),
SORT KEY (when_clicked)
);

The query engine would internally convert the standard CREATE TABLE syntax to equivalent columnstore-specific CREATE TABLE syntax, as follows:

CREATE TABLE webpage_visits(
id BIGINT AUTO_INCREMENT,
user_id BIGINT,
page_id INT,
when_clicked DATETIME,
UNIQUE KEY `PRIMARY` (id) USING HASH,
KEY (user_id) USING HASH,
KEY (page_id) USING HASH,
SORT KEY (when_clicked)
);

Last modified: April 6, 2023

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