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ScyllaDB Docs ScyllaDB Open Source CQL Reference Data Definition

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Data Definition¶

CQL stores data in tables, whose schema defines the layout of said data in the table, and those tables are grouped in keyspaces. A keyspace defines a number of options that apply to all the tables it contains, most prominently of which is the replication strategy used by the keyspace. An application can have only one keyspace. However, it is also possible to have multiple keyspaces in case your application has different replication requirements.

Note

Schema updates require at least a quorum of nodes in a cluster to be available. If the quorum is lost, it must be restored before a schema is updated. See Handling Node Failures for details.

This section describes the statements used to create, modify, and remove keyspaces and tables.

CREATE KEYSPACE

USE

ALTER KEYSPACE

DROP KEYSPACE

CREATE TABLE

ALTER TABLE

DROP TABLE

TRUNCATE

Common Definitions¶

Keyspace and table names are defined by the following grammar:

keyspace_name: `name`
table_name: [ `keyspace_name` '.' ] `name`
name: `unquoted_name` | `quoted_name`
unquoted_name: re('[a-zA-Z_0-9]{1, 48}')
quoted_name: '"' `unquoted_name` '"'

Both keyspace and table names consist of only alphanumeric characters, cannot be empty, and are limited in size to 48 characters (that limit exists mostly to avoid filenames, which may include the keyspace and table name, to go over the limits of certain file systems). By default, keyspace and table names are case insensitive (myTable is equivalent to mytable), but case sensitivity can be forced by using double-quotes ("myTable" is different from mytable).

Further, a table is always part of a keyspace, and a table name can be provided fully-qualified by the keyspace it is part of. If it is not fully-qualified, the table is assumed to be in the current keyspace (see USE statement).

Further, valid column names are simply defined as:

column_name: `identifier`

We also define the notion of statement options for use in the following section:

options: `option` ( AND `option` )*
option: `identifier` '=' ( `identifier` | `constant` | `map_literal` )

In all cases, for creating keyspaces and tables, if you are using Reserved Keywords, enclose them in single or double-quotes.

CREATE KEYSPACE¶

A keyspace is created using a CREATE KEYSPACE statement:

create_keyspace_statement: CREATE KEYSPACE [ IF NOT EXISTS ] `keyspace_name` WITH `options`

For example:

CREATE KEYSPACE Excalibur
WITH replication = {'class': 'NetworkTopologyStrategy', 'DC1' : 1, 'DC2' : 3}
AND durable_writes = true;

The supported options are:

name

kind

mandatory

default

description

replication

map

yes

The replication strategy and options to use for the keyspace (see details below).

durable_writes

simple

no

true

Whether to use the commit log for updates on this keyspace (disable this option at your own risk!).

tablets

map

no

Enables or disables tablets for the keyspace (see tablets)

The replication property is mandatory and must at least contains the 'class' sub-option, which defines the replication strategy class to use. The rest of the sub-options depend on what replication strategy is used. By default, ScyllaDB supports the following 'class':

SimpleStrategy¶

A simple strategy that defines a replication factor for data to be spread across the entire cluster. This is generally not a wise choice for production because it does not respect datacenter layouts and can lead to wildly varying query latency. For a production ready strategy, see NetworkTopologyStrategy . SimpleStrategy supports a single mandatory argument:

sub-option

type

since

description

'replication_factor'

int

all

The number of replicas to store per range.

The replication factor should be equal to or lower than the number of nodes. Configuring a higher RF may prevent creating tables in that keyspace.

Note

Using NetworkTopologyStrategy is recommended. Using SimpleStrategy will make it harder to add Data Center in the future.

NetworkTopologyStrategy¶

A production ready replication strategy that allows to set the replication factor independently for each data-center. The rest of the sub-options are key-value pairs where a key is a data-center name and its value is the associated replication factor. Options:

sub-option

type

description

'<datacenter>'

int

The number of replicas to store per range in the provided datacenter.

'replication_factor'

int

The number of replicas to use as a default per datacenter if not specifically provided. Note that this always defers to existing definitions or explicit datacenter settings. For example, to have three replicas per datacenter, supply this with a value of 3.

The replication factor configured for a DC should be equal to or lower than the number of nodes in that DC. Configuring a higher RF may prevent creating tables in that keyspace.

Note that when ALTER ing keyspaces and supplying replication_factor, auto-expansion will only add new datacenters for safety, it will not alter existing datacenters or remove any even if they are no longer in the cluster. If you want to remove datacenters while still supplying replication_factor, explicitly zero out the datacenter you want to have zero replicas.

An example of auto-expanding datacenters with two datacenters: DC1 and DC2:

CREATE KEYSPACE excalibur
    WITH replication = {'class': 'NetworkTopologyStrategy', 'replication_factor' : 3}

DESCRIBE KEYSPACE excalibur
    CREATE KEYSPACE excalibur WITH replication = {'class': 'NetworkTopologyStrategy', 'DC1': '3', 'DC2': '3'} AND durable_writes = true;

An example of auto-expanding and overriding a datacenter:

CREATE KEYSPACE excalibur
    WITH replication = {'class': 'NetworkTopologyStrategy', 'replication_factor' : 3, 'DC2': 2}

DESCRIBE KEYSPACE excalibur
    CREATE KEYSPACE excalibur WITH replication = {'class': 'NetworkTopologyStrategy', 'DC1': '3', 'DC2': '2'} AND durable_writes = true;

An example that excludes a datacenter while using replication_factor:

CREATE KEYSPACE excalibur
    WITH replication = {'class': 'NetworkTopologyStrategy', 'replication_factor' : 3, 'DC2': 0} ;

DESCRIBE KEYSPACE excalibur
    CREATE KEYSPACE excalibur WITH replication = {'class': 'NetworkTopologyStrategy', 'DC1': '3'} AND durable_writes = true;

Keyspace storage options Experimental¶

By default, SStables of a keyspace are stored locally. As an alternative, you can configure your keyspace to be stored on Amazon S3 or another S3-compatible object store. See Keyspace storage options for details.

The tablets property¶

The tablets property enables or disables tablets-based distribution for a keyspace.

Options:

sub-option

type

description

'enabled'

bool

Whether or not to enable tablets for a keyspace

'initial'

int

The number of tablets to start with

By default, a keyspace is created with tablets enabled. The tablets option is used to opt out a keyspace from tablets-based distribution; see Enabling Tablets for details.

A good rule of thumb to calculate initial tablets is to divide the expected total storage used by tables in this keyspace by (replication_factor * 5GB). For example, if you expect a 30TB table and have a replication factor of 3, divide 30TB by (3*5GB) for a result of 2000. Since the value must be a power of two, round up to 2048. The calculation applies to every table in the keyspace.

An example that creates a keyspace with 2048 tablets per table:

CREATE KEYSPACE excalibur
WITH replication = {
    'class': 'NetworkTopologyStrategy',
    'replication_factor': 3,
} AND tablets = {
    'initial': 2048
};

See Data Distribution with Tablets for more information about tablets.

USE¶

The USE statement allows you to change the current keyspace (for the connection on which it is executed). Some objects in CQL are bound to a keyspace (tables, user-defined types, functions, …), and the current keyspace is the default keyspace used when those objects are referred without a fully-qualified name (that is, without being prefixed a keyspace name). A USE statement simply takes the specified keyspace and uses the name as an argument for all future actions until this name is changed.

use_statement: USE `keyspace_name`

ALTER KEYSPACE¶

An ALTER KEYSPACE statement lets you modify the options of a keyspace:

alter_keyspace_statement: ALTER KEYSPACE `keyspace_name` WITH `options`

For instance:

ALTER KEYSPACE Excelsior
 WITH replication = { 'class' : 'NetworkTopologyStrategy', 'dc1' : 3, 'dc2' : 0};

The supported options are the same as creating a keyspace.

ALTER KEYSPACE with Tablets Experimental¶

Modifying a keyspace with tablets enabled is possible and doesn’t require any special CQL syntax. However, there are some limitations:

  • The replication factor (RF) can be increased or decreased by at most 1 at a time. To reach the desired RF value, modify the RF repeatedly.

  • The ALTER statement rejects the replication_factor tag. List the DCs explicitly when altering a keyspace. See NetworkTopologyStrategy.

  • If there’s any other ongoing global topology operation, executing the ALTER statement will fail (with an explicit and specific error) and needs to be repeated.

  • The ALTER statement may take longer than the regular query timeout, and even if it times out, it will continue to execute in the background.

  • The replication strategy cannot be modified, as keyspaces with tablets only support NetworkTopologyStrategy.

DROP KEYSPACE¶

Dropping a keyspace can be done using the DROP KEYSPACE statement:

drop_keyspace_statement: DROP KEYSPACE [ IF EXISTS ] `keyspace_name`

For instance:

DROP KEYSPACE Excelsior;

Dropping a keyspace results in the immediate removal of that keyspace, including all the tables, UTD and functions in it, and all the data contained in those tables.

Note

By default, when a table or a keyspace is removed, a snapshot is taken so that you can restore it later. As a result, the disk space remains the same and is not immediately reclaimed. Refer to this article or this FAQ entry.

If the keyspace does not exist, the statement will return an error unless IF EXISTS is used, in which case the operation is a no-op.

CREATE TABLE¶

Creating a new table uses the CREATE TABLE statement:

create_table_statement: CREATE TABLE [ IF NOT EXISTS ] `table_name`
                      : '('
                      :     `column_definition`
                      :     ( ',' `column_definition` )*
                      :     [ ',' PRIMARY KEY '(' `primary_key` ')' ]
                      : ')' [ WITH `table_options` ]

column_definition: `column_name` `cql_type` [ STATIC ] [ PRIMARY KEY]

primary_key: `partition_key` [ ',' `clustering_columns` ]

partition_key: `column_name`
             : | '(' `column_name` ( ',' `column_name` )* ')'

clustering_columns: `column_name` ( ',' `column_name` )*

table_options: COMPACT STORAGE [ AND `table_options` ]
                : | CLUSTERING ORDER BY '(' `clustering_order` ')' [ AND `table_options` ]
                : | scylla_encryption_options: '=' '{'[`cipher_algorithm` : <hash>]','[`secret_key_strength` : <len>]','[`key_provider`: <provider>]'}'
                : | caching  '=' ' {'caching_options'}'
                : | `options`

clustering_order: `column_name` (ASC | DESC) ( ',' `column_name` (ASC | DESC) )*

For instance:

 CREATE TABLE monkeySpecies (
     species text PRIMARY KEY,
     common_name text,
     population varint,
     average_size int
 ) WITH comment='Important biological records';

 CREATE TABLE timeline (
     userid uuid,
     posted_month int,
     posted_time uuid,
     body text,
     posted_by text,
     PRIMARY KEY (userid, posted_month, posted_time)
 ) WITH compaction = { 'class' : 'LeveledCompactionStrategy' };

 CREATE TABLE loads (
     machine inet,
     cpu int,
     mtime timeuuid,
     load float,
     PRIMARY KEY ((machine, cpu), mtime)
 ) WITH CLUSTERING ORDER BY (mtime DESC);

 CREATE TABLE users_picture (
     userid uuid,
     pictureid uuid,
     body text,
     posted_by text,
     PRIMARY KEY (userid, pictureid, posted_by)
 ) WITH compression = {'sstable_compression': 'LZ4Compressor'};


 CREATE TABLE data_atrest (
     pk text PRIMARY KEY,
     c0 int
 ) WITH scylla_encryption_options = {
    'cipher_algorithm' : 'AES/ECB/PKCS5Padding',
    'secret_key_strength' : 128,
    'key_provider': 'LocalFileSystemKeyProviderFactory',
    'secret_key_file': '/etc/scylla/data_encryption_keys/secret_key'};

CREATE TABLE caching (
                 k int PRIMARY KEY,
                 v1 int,
                 v2 int,
             ) WITH caching = {'enabled': 'true'};

A CQL table has a name and is composed of a set of rows. Creating a table amounts to defining which columns the rows will be composed, which of those columns compose the primary key, as well as optional options for the table.

Attempting to create an already existing table will return an error unless the IF NOT EXISTS directive is used. If it is used, the statement will be a no-op if the table already exists.

Column definitions¶

Every row in a CQL table has a set of predefined columns defined at the time of the table creation (or added later using an alter statement).

A column_definition is primarily comprised of the name of the column defined and its type, which restricts which values are accepted for that column. Additionally, a column definition can have the following modifiers:

STATIC

declares the column as being a static column.

PRIMARY KEY

declares the column as being the sole component of the primary key of the table.

Static columns¶

Some columns can be declared as STATIC in a table definition. A column that is static will be “shared” by all the rows belonging to the same partition (having the same partition key). For instance:

CREATE TABLE t (
    pk int,
    t int,
    v text,
    s text static,
    PRIMARY KEY (pk, t)
);

INSERT INTO t (pk, t, v, s) VALUES (0, 0, 'val0', 'static0');
INSERT INTO t (pk, t, v, s) VALUES (0, 1, 'val1', 'static1');

SELECT * FROM t;
   pk | t | v      | s
  ----+---+--------+-----------
   0  | 0 | 'val0' | 'static1'
   0  | 1 | 'val1' | 'static1'

As can be seen, the s value is the same (static1) for both of the rows in the partition (the partition key in that example being pk, both rows are in that same partition): the 2nd insertion has overridden the value for s.

Static columns have the following restrictions:

  • tables with the COMPACT STORAGE option (see below) cannot use them.

  • a table without clustering columns cannot have static columns (in a table without clustering columns, every partition has only one row, and so every column is inherently static).

  • only non PRIMARY KEY columns can be static.

The Primary key¶

Within a table, a row is uniquely identified by its PRIMARY KEY, and hence all tables must define a PRIMARY KEY (and only one). A PRIMARY KEY definition is composed of one or more of the columns defined in the table. Syntactically, the primary key is defined by the keywords PRIMARY KEY, followed by a comma-separated list of the column names composing it within parenthesis. However, if the primary key has only one column, one can alternatively follow that column definition by the PRIMARY KEY keywords. The order of the columns in the primary key definition matter.

A CQL primary key is composed of 2 parts:

  • the partition key part. It is the first component of the primary key definition. It can be a single column or, using additional parenthesis, can be multiple columns. A table always has at least a partition key, the smallest possible table definition is:

    CREATE TABLE t (k text PRIMARY KEY);
    
  • the clustering columns. Those are the columns after the first component of the primary key definition, and the order of those columns define the clustering order.

Some examples of primary key definition are:

  • PRIMARY KEY (a): a is the partition key, and there are no clustering columns.

  • PRIMARY KEY (a, b, c): a is the partition key, and b and c are the clustering columns.

  • PRIMARY KEY ((a, b), c): a and b compose the partition key (this is often called a composite partition key), and c is the clustering column.

Note

A null value is not allowed as any partition-key or clustering-key column. A Null value is not the same as an empty string.

The partition key¶

Within a table, CQL defines the notion of a partition. A partition is simply the set of rows that share the same value for their partition key. Note that if the partition key is composed of multiple columns, then rows belong to the same partition only when they have the same values for all those partition key columns. So, for instance, given the following table definition and content:

CREATE TABLE t (
    a int,
    b int,
    c int,
    d int,
    PRIMARY KEY ((a, b), c, d)
);

SELECT * FROM t;
   a | b | c | d
  ---+---+---+---
   0 | 0 | 0 | 0    // row 1
   0 | 0 | 1 | 1    // row 2
   0 | 1 | 2 | 2    // row 3
   0 | 1 | 3 | 3    // row 4
   1 | 1 | 4 | 4    // row 5

row 1 and row 2 are in the same partition, row 3 and row 4 are also in the same partition (but a different one) and row 5 is in yet another partition.

Note that a table always has a partition key and that if the table has no clustering columns, then every partition of that table is only comprised of a single row (since the primary key uniquely identifies rows and the primary key is equal to the partition key if there are no clustering columns).

The most important property of partition is that all the rows belonging to the same partition are guarantee to be stored on the same set of replica nodes. In other words, the partition key of a table defines which of the rows will be localized together in the cluster, and it is thus important to choose your partition key wisely so that rows that need to be fetched together are in the same partition (so that querying those rows together require contacting a minimum of nodes).

However, please note that there is a flip-side to this guarantee: as all rows sharing a partition key are guaranteed to be stored on the same set of replica nodes, a partition key that groups too much data can create a hotspot.

Another useful property of a partition is that when writing data, all the updates belonging to a single partition are done atomically and in isolation, which is not the case across partitions.

The proper choice of the partition key and clustering columns for a table is probably one of the most important aspects of data modeling in ScyllaDB. It largely impacts which queries can be performed and how efficient they are.

Note

An empty string is not allowed as a partition key value. In a compound partition key (multiple partition-key columns), any or all of them may be empty strings. Empty string is not a Null value.

The clustering columns¶

The clustering columns of a table define the clustering order for the partition of that table. For a given partition, all the rows are physically ordered inside ScyllaDB by that clustering order. For instance, given:

CREATE TABLE t (
    a int,
    b int,
    c int,
    PRIMARY KEY (a, b, c)
);

SELECT * FROM t;
   a | b | c
  ---+---+---
   0 | 0 | 4     // row 1
   0 | 1 | 9     // row 2
   0 | 2 | 2     // row 3
   0 | 3 | 3     // row 4

then the rows (which all belong to the same partition) are all stored internally in the order of the values of their b column (the order they are displayed above). So, where the partition keys of the table let you group rows on the same replica set, the clustering columns control how those rows are stored on the replica. That sorting allows the retrieval of a range of rows within a partition (for instance, in the example above, SELECT * FROM t WHERE a = 0 AND b > 1 and b <= 3) is very efficient.

Note

An empty string is allowed as a clustering key value. Empty string is not a Null value.

Table options¶

A CQL table has a number of options that can be set at creation (and, for most of them, altered later). These options are specified after the WITH keyword.

Amongst those options, two important ones cannot be changed after creation and influence which queries can be done against the table: the COMPACT STORAGE option and the CLUSTERING ORDER option. Those, as well as the other options of a table are described in the following sections.

Compact tables¶

A compact table is one defined with the COMPACT STORAGE option. This option is only maintained for backward compatibility for definitions created before CQL version 3 and shouldn’t be used for new tables. Declaring a table with this option creates limitations for the table, which are largely arbitrary (and exists for historical reasons). Amongst these limitations:

  • a compact table cannot use collections nor static columns.

  • if a compact table has at least one clustering column, then it must have exactly one column outside of the primary key ones. This implies that you cannot add or remove columns in particular after creation.

  • a compact table is limited as to the indexes it can create, and no materialized view can be created on it.

Reversing the clustering order¶

The clustering order of a table is defined by the clustering columns of that table. By default, that ordering is based on the natural order of the clustering order, but the CLUSTERING ORDER lets you change that clustering order to use the reverse natural order for some (potentially all) of the columns.

The CLUSTERING ORDER option takes the comma-separated list of the clustering column, each with an ASC (for ascendant, e.g. the natural order) or DESC (for descendant, e.g. the reverse natural order). Note in particular that the default (if the CLUSTERING ORDER option is not used) is strictly equivalent to using the option with all clustering columns using the ASC modifier.

Note that this option is basically a hint for the storage engine to change the order in which it stores the row, but it has three visible consequences:

  • it limits which ORDER BY clause is allowed for selects on that table. You can only order results by the clustering order or the reverse clustering order. Meaning that if a table has two clustering columns a and b, and you define WITH CLUSTERING ORDER (a DESC, b ASC), then in queries, you will be allowed to use ORDER BY (a DESC, b ASC) and (reverse clustering order) ORDER BY (a ASC, b DESC) but not ORDER BY (a ASC, b ASC) (nor ORDER BY (a DESC, b DESC)).

  • it also changes the default order of results when queried (if no ORDER BY is provided). Results are always returned in clustering order (within a partition).

  • it has a small performance impact on some queries as queries in reverse clustering order are slower than the one in forward clustering order. In practice, this means that if you plan on querying mostly in the reverse natural order of your columns (which is common with time series, for instance, where you often want data from the newest to the oldest), it is an optimization to declare a descending clustering order.

Other table options¶

A table supports the following options:

Option

Kind

Default

Description

comment

simple

none

A free-form, human-readable comment.

speculative_retry

simple

99PERCENTILE

Speculative retry options

gc_grace_seconds

simple

864000

Time to wait before garbage collecting tombstones (deletion markers). See Tombstones GC options.

tombstone_gc

mode

see below

The mode of garbage collecting tombstones. See Tombstones GC options.

bloom_filter_fp_chance

simple

0.01

The target probability of false-positive of the sstable bloom filters. Sstable bloom filters will be sized to provide the provided probability (thus lowering this value impact the size of bloom filters in-memory and on-disk).

default_time_to_live

simple

0

The default expiration time (“TTL”) in seconds for a table.

compaction

map

see below

Compaction options

compression

map

see below

Compression options

caching

map

see below

Caching Options

cdc

map

see below

CDC Options

Speculative retry options¶

By default, ScyllaDB read coordinators only query as many replicas as necessary to satisfy consistency levels: one for consistency level ONE, a quorum for QUORUM, and so on. speculative_retry determines when coordinators may query additional replicas, which is useful when replicas are slow or unresponsive. The following are legal values (case-insensitive):

Format

Example

Description

XPERCENTILE

90.5PERCENTILE

Coordinators record average per-table response times for all replicas. If a replica takes longer than X percent of this table’s average response time, the coordinator queries an additional replica. X must be between 0 and 100.

XP

90.5P

Synonym for XPERCENTILE

Yms

25ms

If a replica takes more than Y milliseconds to respond, the coordinator queries an additional replica.

ALWAYS

Coordinators always query all replicas.

NONE

Coordinators never query additional replicas.

This setting does not affect reads with consistency level ALL because they already query all replicas.

Note that frequently reading from additional replicas can hurt cluster performance. When in doubt, keep the default 99PERCENTILE.

Compaction options¶

The compaction options must at least define the 'class' sub-option, which defines the compaction strategy class to use. The default supported class are 'SizeTieredCompactionStrategy', 'LeveledCompactionStrategy', and 'IncrementalCompactionStrategy'. Custom strategy can be provided by specifying the full class name as a string constant.

All default strategies support a number of common options, as well as options specific to the strategy chosen (see the section corresponding to your strategy for details: STCS, LCS, and TWCS).

Compression options¶

The compression options define if and how the sstables of the table are compressed. The following sub-options are available:

Option

Default

Description

sstable_compression

LZ4Compressor

The compression algorithm to use. Available compressors are LZ4Compressor, SnappyCompressor, DeflateCompressor, and ZstdCompressor.

chunk_length_in_kb

4

On disk SSTables are compressed by block (to allow random reads). This defines the size (in KB) of the block. Bigger values may improve the compression rate, but increases the minimum size of data to be read from disk for a read. Allowed values are powers of two between 1 and 128.

For example, to enable compression:

CREATE TABLE id (id int PRIMARY KEY) WITH compression = {'sstable_compression': 'LZ4Compressor'};

For example, to disable compression:

CREATE TABLE id (id int PRIMARY KEY) WITH compression = {};
CDC options¶

The following options can be used with Change Data Capture.

option

default

description

enabled

false

When set to true, another table — the CDC log table — is created and associated with the table you are creating/altering (for example, customer_data). All writes made to this table (customer_data) are reflected in the corresponding CDC log table.

preimage

false

When set to true, it saves the result of what a client performing a write would display if it has queried this table before making the write into the corresponding CDC log table.

ttl

86400 seconds 24 hours

Time after which data stored in CDC will be removed and won’t be accessible to the client anymore.

For example:

CREATE TABLE customer_data (
    cust_id uuid,
    cust_first-name text,
    cust_last-name text,
    cust_phone text,
    cust_get-sms text,
    PRIMARY KEY (customer_id)
) WITH cdc = { 'enabled' : 'true', 'preimage' : 'true' };
Caching options¶

Caching optimizes cache memory usage of a table. The cached data is weighed by size and access frequency.

option

default

description

enabled

TRUE

When set to TRUE enables caching on the specified table. Valid options are TRUE and FALSE.

For example,

CREATE TABLE caching (
                 k int PRIMARY KEY,
                 v1 int,
                 v2 int,
             ) WITH caching = {'enabled': 'true'};
Tombstones GC options¶

ScyllaDB inherited the gc_grace_seconds option from Apache Cassandra. The option allows you to specify the wait time (in seconds) before data marked with a deletion tombstone is removed via compaction. This option assumes that you run repair during the specified time. Failing to run repair during the wait time may result in the resurrection of deleted data.

The tombstone_gc option allows you to prevent data resurrection. With the repair mode configured, tombstone are only removed after repair is performed. Unlike gc_grace_seconds, tombstone_gc has no time constraints - when the repair mode is on, tombstones garbage collection will wait until repair is run. For tables which use tablets repair mode is set by default.

You can enable the after-repair tombstone GC by setting the repair mode using ALTER TABLE or CREATE TABLE. For example:

CREATE TABLE ks.cf (key blob PRIMARY KEY,  val blob) WITH tombstone_gc = {'mode':'repair'};
ALTER TABLE ks.cf WITH tombstone_gc = {'mode':'repair'} ;

The following modes are available:

Mode

Description

timeout

Tombstone GC is performed after the wait time specified with gc_grace_seconds (default).

repair

Tombstone GC is performed after repair is run.

disabled

Tombstone GC is never performed. This mode may be useful when loading data to the database, to avoid tombstone GC when part of the data is not yet available.

immediate

Tombstone GC is immediately performed. There is no wait time or repair requirement. This mode is useful for a table that uses the TWCS compaction strategy with no user deletes. After data is expired after TTL, ScyllaDB can perform compaction to drop the expired data immediately.

Other considerations:¶
  • Adding new columns (see ALTER TABLE below) is a constant time operation. There is thus no need to try to anticipate future usage when creating a table.

Limiting the rate of requests per partition¶

You can limit the read rates and writes rates into a partition by applying a ScyllaDB CQL extension to the CREATE TABLE or ALTER TABLE statements. See Per-partition rate limit for details.

ALTER TABLE¶

Altering an existing table uses the ALTER TABLE statement:

alter_table_statement: ALTER TABLE `table_name` `alter_table_instruction`
alter_table_instruction: ADD `column_name` `cql_type` ( ',' `column_name` `cql_type` )*
                       : | DROP `column_name` [ USING TIMESTAMP `timestamp` ]
                       : | DROP '(' `column_name` ( ',' `column_name` )* ')' [ USING TIMESTAMP `timestamp` ]
                       : | ALTER `column_name` TYPE `cql_type`
                       : | WITH `options`
                       : | scylla_encryption_options: '=' '{'[`cipher_algorithm` : <hash>]','[`secret_key_strength` : <len>]','[`key_provider`: <provider>]'}'

For instance:

ALTER TABLE addamsFamily ADD gravesite varchar;

ALTER TABLE addamsFamily
       WITH comment = 'A most excellent and useful table';


ALTER TABLE data_atrest (
    pk text PRIMARY KEY,
    c0 int
) WITH scylla_encryption_options = {
   'cipher_algorithm' : 'AES/ECB/PKCS5Padding',
   'secret_key_strength' : 128,
   'key_provider': 'LocalFileSystemKeyProviderFactory',
   'secret_key_file': '/etc/scylla/data_encryption_keys/secret_key'};

ALTER TABLE customer_data
   WITH cdc = { 'enabled' : 'true', 'preimage' : 'true' };

The ALTER TABLE statement can:

  • Add new column(s) to the table (through the ADD instruction). Note that the primary key of a table cannot be changed, and thus newly added column will, by extension, never be part of the primary key. Also, note that compact tables have restrictions regarding column addition. Note that this is constant (in the amount of data the cluster contains) time operation.

  • Remove column(s) from the table. This drops both the column and all its content, but note that while the column becomes immediately unavailable, its content is only removed lazily during compaction. Please also note the warnings below. Due to lazy removal, the altering itself is a constant (in the amount of data removed or contained in the cluster) time operation.

  • Change data type of the column to a compatible type.

  • Change some of the table options (through the WITH instruction). The supported options are the same that when creating a table (outside of COMPACT STORAGE and CLUSTERING ORDER that cannot be changed after creation). Note that setting any compaction sub-options has the effect of erasing all previous compaction options, so you need to re-specify all the sub-options if you want to keep them. The same note applies to the set of compression sub-options.

  • Change or add any of the Encryption options above.

  • Change or add any of the CDC options above.

  • Change or add per-partition rate limits. See Limiting the rate of requests per partition.

Warning

Dropping a column assumes that the timestamps used for the value of this column are “real” timestamp in microseconds. Using “real” timestamps in microseconds is the default is and is strongly recommended, but as ScyllaDB allows the client to provide any timestamp on any table, it is theoretically possible to use another convention. Please be aware that if you do so, dropping a column will not work correctly.

Warning

Once a column is dropped, it is allowed to re-add a column with the same name as the dropped one unless the type of the dropped column was a (non-frozen) column (due to an internal technical limitation).

It is also possible to drop a column with specified timestamp ALTER TABLE ... DROP ... USING TIMESTAMP .... The purpose of this statement is to be able to safely restore schema (see Backup and Restore Procedures) in the case a column was dropped and re-added later. The timestamp should be obtained by describing schema with internals DESC SCHEMA WITH INTERNALS (or other descriptions like DESC TABLE ks.cf WITH INTERNALS)

For example: Let’s say you have a table with some data. Then you drop one of the column and re-add it later. In the future, when you wish to restore the schema, you have to also drop the column with specified timestamp (the same timestamp as the original drop) and re-add it again. Otherwise, you can resurrect your data (if you skip ALTER ... DROP/ADD ... entirely) or you can lose data inserted after column re-addition (if you drop the column without the timestamp).

Warning

Dropping a column with specified timestamp should only be used to restore schema from description (DESCRIBE SCHEMA WITH INTERNALS).

DROP TABLE¶

Dropping a table uses the DROP TABLE statement:

drop_table_statement: DROP TABLE [ IF EXISTS ] `table_name`

Dropping a table results in the immediate removal of the table, including all data it contains and any associated secondary indexes.

Note

By default, when a table or a keyspace is removed, a snapshot is taken so that you can restore it later. As a result, the disk space remains the same and is not immediately reclaimed. Refer to this article or this FAQ entry.

If the table does not exist, the statement will return an error unless IF EXISTS is used, in which case the operation is a no-op.

Note

Dropping a table that has materialized views is disallowed and will return an error. To do so, the materialized views that depend on the table must first be explicitly dropped. Refer to Materialized Views for details.

TRUNCATE¶

A table can be truncated using the TRUNCATE statement:

truncate_statement: TRUNCATE [ TABLE ] `table_name`
                  : [ USING TIMEOUT `timeout` ]
timeout: `duration`

Note that TRUNCATE TABLE foo is allowed for consistency with other DDL statements, but tables are the only object that can be truncated currently and so the TABLE keyword can be omitted.

Truncating a table permanently removes all existing data from the table, but without removing the table itself.

The USING TIMEOUT clause allows specifying a timeout for a specific request.

For example:

TRUNCATE TABLE users USING TIMEOUT 5m;

Caution

Do not run any operation on a table that is being truncated. Truncate operation is an administrative operation, and running any other operation on the same table in parallel may cause the truncating table’s data to end up in an undefined state.

  • Apache Cassandra Query Language (CQL) Reference

Copyright

© 2016, The Apache Software Foundation.

Apache®, Apache Cassandra®, Cassandra®, the Apache feather logo and the Apache Cassandra® Eye logo are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by The Apache Software Foundation is implied by the use of these marks.

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