Was this page helpful?
Caution
You're viewing documentation for an unstable version of ScyllaDB Enterprise. Switch to the latest stable version.
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.
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.
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 |
---|---|---|---|---|
|
map |
yes |
The replication strategy and options to use for the keyspace (see details below). |
|
|
simple |
no |
true |
Whether to use the commit log for updates on this keyspace (disable this option at your own risk!). |
|
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'
:
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 |
---|---|---|---|
|
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.
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 |
---|---|---|
|
int |
The number of replicas to store per range in the provided datacenter. |
|
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;
tablets
property¶The tablets
property enables or disables tablets-based distribution
for a keyspace.
Options:
sub-option |
type |
description |
---|---|---|
|
bool |
Whether or not to enable tablets for a keyspace |
|
int |
The number of tablets to start with |
By default, a keyspace is created with tablets disabled on the keyspace level. Tables in keyspaces created with default settings will not utilize tablets.
To use tablets, create a new keyspace with the tablets = { 'enabled': true }
option. For example:
CREATE KEYSPACE my_keyspace
WITH replication = {
'class': 'NetworkTopologyStrategy',
'replication_factor': 3
} AND tablets = {
'enabled': true
};
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.
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`
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.
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
.
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
A table supports the following options:
Option |
Kind |
Default |
Description |
---|---|---|---|
|
simple |
none |
A free-form, human-readable comment. |
|
simple |
99PERCENTILE |
|
|
simple |
864000 |
Time to wait before garbage collecting tombstones (deletion markers). See Tombstones GC options. |
|
mode |
see below |
The mode of garbage collecting tombstones. See Tombstones GC options. |
|
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). |
|
simple |
0 |
The default expiration time (“TTL”) in seconds for a table. |
|
simple |
0 |
Flush the memtables associated with this table every |
|
simple |
128 |
Minimum gap between summary entries: ScyllaDB will create summary entries with at least this amount of partitions between them. Controls the maximums density of the summary. |
|
simple |
2048 |
Not implemented (option value is ignored). |
|
map |
see below |
|
|
map |
see below |
|
|
map |
see below |
|
|
map |
see below |
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 |
---|---|---|
|
90.5PERCENTILE |
Coordinators record average per-table response times for all replicas.
If a replica takes longer than |
|
90.5P |
Synonym for |
|
25ms |
If a replica takes more than |
|
Coordinators always query all replicas. |
|
|
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
.
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, ICS, and TWCS).
The compression
options define if and how the sstables of the table are compressed. The following sub-options are
available:
Option |
Default |
Description |
---|---|---|
|
LZ4Compressor |
The compression algorithm to use. Available compressors are LZ4Compressor, SnappyCompressor, DeflateCompressor, and ZstdCompressor. |
|
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. |
|
1.0 |
Not implemented (option value is ignored). |
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 = {};
The following options can be used with Change Data Capture.
option |
default |
description |
---|---|---|
|
|
When set to |
|
|
When set to |
|
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 optimizes cache memory usage of a table. The cached data is weighed by size and access frequency.
option |
default |
description |
---|---|---|
|
|
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'};
Encryption options are used when enabling or disabling encryption at rest, available in Scylla Enterprise from version 2019.1.1.
Note
When the key_provider
is LocalFileSystemKeyProviderFactory
, you must indicate where the key resides using the secret_key_file: <path>
parameter. Refer to Encryption at Rest for details.
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 |
---|---|
|
Tombstone GC is performed after the wait time specified with |
|
Tombstone GC is performed after repair is run. |
|
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. |
|
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. |
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.
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.
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
).
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.
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.
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.
Was this page helpful?