Project: Scylla (App Definition and Development / Database)
File: cql-extensions.md

ScyllaDB extends the CQL language to provide a few extra features. This document lists those extensions. The `BYPASS CACHE` clause on `SELECT` statements informs the database that the data being read is unlikely to be read again in the near future, and also was unlikely to have been read in the near past; therefore no attempt should be made to read it from the cache or to populate the cache with the data. This is mostly useful for range scans; these typically process large amounts of data with no temporal locality and do not benefit from the cache. The clause is placed immediately after the optional `ALLOW FILTERING` clause: SELECT ... FROM ... WHERE ... ALLOW FILTERING -- optional BYPASS CACHE The `paxosgraceseconds` option is used to set the amount of seconds which are used to TTL data in paxos tables when using LWT queries against the base table. This value is intentionally decoupled from `gcgraceseconds` since, in general, the base table could use completely different strategy to garbage collect entries, e.g. can set `gcgraceseconds` to 0 if it doesn't use deletions and hence doesn't need to repair. However, paxos tables still rely on repair to achieve consistency, and the user is required to execute repair within `paxosgraceseconds`. Default value is equal to `DEFAULTGCGRACE_SECONDS`, which is 10 days. The option can be specified at `CREATE TABLE` or `ALTER TABLE` queries in the same way as other options by using `WITH` clause: CREATE TABLE tbl ... WITH paxosgraceseconds=1234 TIMEOUT extension allows specifying per-query timeouts. This parameter accepts a single duration and applies it as a timeout specific to a single particular query. The parameter is supported for prepared statements as well. The parameter acts as part of the USING clause, and thus can be combined with other parameters - like timestamps and time-to-live. For example, one can use ``USING TIMEOUT ... and TTL ...`` to specify both a non-default timeout and a ttl. Examples: ```cql SELECT * FROM t USING TIMEOUT 200ms; ``` ```cql INSERT INTO t(a,b,c) VALUES (1,2,3) USING TIMESTAMP 42 AND TIMEOUT 50ms; ``` ```cql TRUNCATE TABLE t USING TIMEOUT 5m; ``` Working with prepared statements works as usual - the timeout parameter can be explicitly defined or provided as a marker: ```cql SELECT * FROM t USING TIMEOUT ?; ``` ```cql INSERT INTO t(a,b,c) VALUES (?,?,?) USING TIMESTAMP 42 AND TIMEOUT 50ms; ``` The timeout parameter can be applied to the following data modification queries: INSERT, UPDATE, DELETE, PRUNE MATERIALIZED VIEW, BATCH, and to the TRUNCATE data definition query. In addition, the timeout parameter can be applied to SELECT queries as well. ```{eval-rst} .. _keyspace-storage-options: ``` <! This section must be moved to Data Definition> CREATE KEYSPACE when support for object storage is GA. > By default, SStables of a keyspace are stored in a local directory. As an alternative, you can configure your keyspace to be stored on Amazon S3 or another S3-compatible object store. Support for object storage is experimental and must be explicitly enabled in the ``scylla.yaml`` configuration file by specifying the ``keyspace-storage-options`` option: ``` experimental_features: keyspace-storage-options ``` With support for object storage enabled, add your endpoint configuration to ``scylla.yaml``: Create an ``object-storage-config-file.yaml`` file with a description of allowed endpoints, for example: ``` endpoints: name: $endpointaddressordomainname port: $port_number https: optional True or False aws_region: optional region name,

us-east-1 awsaccesskey_id: optional AWS access key ID awssecretaccess_key: optional AWS secret access key awssessiontoken: optional AWS session token ``` Specify the ``object-storage-config-file`` option in your ``scylla.yaml``, providing ``object-storage-config-file.yaml`` as the value: ``` object-storage-config-file: object-storage-config-file.yaml ``` Now you can configure your object storage when creating a keyspace: ```cql CREATE KEYSPACE with STORAGE = { 'type': 'S3', 'endpoint': '$endpoint_name', 'bucket': '$bucket' } ``` Example ```cql CREATE KEYSPACE ks WITH REPLICATION = { 'class' : 'NetworkTopologyStrategy', 'replication_factor' : 3 } AND STORAGE = { 'type' : 'S3', 'bucket' : '/tmp/b1', 'endpoint' : 'localhost' } ; ``` Storage options can be inspected by checking the new system schema table: `systemschema.scyllakeyspaces`: ```cql cassandra@cqlsh> select * from systemschema.scyllakeyspaces; keyspacename | storageoptions | storage_type ++-- ksx | {'bucket': '/tmp/xx', 'endpoint': 'localhost'} | S3 ``` A special statement is dedicated for pruning ghost rows from materialized views. Ghost row is an inconsistency issue which manifests itself by having rows in a materialized view which do not correspond to any base table rows. Such inconsistencies should be prevented altogether and ScyllaDB is striving to avoid them, but if they happen, this statement can be used to restore a materialized view to a fully consistent state without rebuilding it from scratch. Example usages: ```cql PRUNE MATERIALIZED VIEW my_view; PRUNE MATERIALIZED VIEW my_view WHERE token(v) > 7 AND token(v) < 1535250; PRUNE MATERIALIZED VIEW my_view WHERE v = 19; ``` The statement works by fetching requested rows from a materialized view and then trying to fetch their corresponding rows from the base table. If it turns out that the base row does not exist, the row is considered a ghost row and is thus deleted. The statement implicitly works with consistency level ALL when fetching from the base table to avoid false positives. As the example shows, a materialized view can be pruned in one go, but one can also specify specific primary keys or token ranges, which is recommended in order to make the operation less heavyweight and allow for running multiple parallel pruning statements for non-overlapping token ranges. Usually, when a table with materialized views is updated, the update to the views happens asynchronously, i.e., in the background. This means that the user cannot know when the view updates have all finished - or even be sure that they succeeded. ScyllaDB allows marking a view as synchronous. When a view is marked synchronous, base-table updates will wait for that view to be updated before returning. A base table may have multiple views marked synchronous, and will wait for all of them. The consistency level of a write applies to synchronous views as well as to the base table: For example, writing with QUORUM consistency level returns only after a quorum of the base-table replicas were updated and also a quorum of each synchronous view table was also updated. Synchronous views tend to reduce the observed availability of the base table, because a base-table write would only succeed if enough synchronous view updates also succeed. On the other hand, failed view updates would be detected immediately, and appropriate action can be taken, such as retrying the write or pruning the materialized view (as mentioned in the previous section). This can improve the consistency of the base table with its views. To create a new materialized view with synchronous updates, use: ```cql CREATE MATERIALIZED VIEW main.mv AS SELECT * FROM

WHERE v IS NOT NULL PRIMARY KEY (v, id) WITH synchronous_updates = true; ``` To make an existing materialized view synchronous, use: ```cql ALTER MATERIALIZED VIEW main.mv WITH synchronous_updates = true; ``` To return a materialized view to the default behavior (which, as explained above, usually means asynchronous updates), use: ```cql ALTER MATERIALIZED VIEW main.mv WITH synchronous_updates = false; ``` Even in an asynchronous view, some view updates may be done synchronously. This happens when the materialized-view replica is on the same node as the base-table replica. This happens, for example, in tables using vnodes where the base table and the view have the same partition key; But is not the case if the table uses tablets: With tablets, the base and view tablets may migrate to different nodes. In general, users should not, and cannot, rely on these serendipitous synchronous view updates; If synchronous view updates are important, mark the view explicitly with `synchronous_updates = true`. Synchronous updates can also be turned on for global secondary indexes. At the time of writing this paragraph there is no direct syntax to do that, but it's possible to mark the underlying materialized view of an index as synchronous. ScyllaDB's implementation of secondary indexes is based on materialized views and the generated view's name can be extracted from schema tables, and is generally constructed by appending `_index` suffix to the index name: ```cql create table main.t(id int primary key, v int); create index on main.t(v); select * from system_schema.indexes ; keyspacename | tablename | index_name | kind | options ++++-- main | t | tvidx | COMPOSITES | {'target': 'v'} (1 rows) select keyspacename, viewname from system_schema.views ; keyspacename | viewname main | tvidx_index (1 rows) alter materialized view tvidxindex with synchronousupdates = true; ``` Local secondary indexes already have synchronous updates, so there's no need to explicitly mark them as such. Scylla aims for a uniform handling of NULL values in expressions, inspired by SQL: The overarching principle is that a NULL signifies an unknown value, so most expressions calculated based on a NULL also results in a NULL. For example, the results of `x + NULL`, `x = NULL` or `x < NULL` are all NULL, no matter what `x` is. Even the expression `NULL = NULL` evaluates to NULL, not TRUE. But not all expressions of NULL evaluate to NULL. An interesting example is boolean conjunction:`FALSE AND NULL` returns FALSE - not NULL. This is because no matter which unknown value the NULL represents, ANDing it with FALSE will always result in FALSE. So the return value is not unknown - it is a FALSE. In contrast, `TRUE AND NULL` does return NULL, because if we AND a TRUE with an unknown value the result is also unknown: `TRUE AND TRUE` is TRUE but `TRUE AND FALSE` is FALSE. Because `x = NULL` always evaluates to NULL, a `SELECT` filter `WHERE x = NULL` matches no row (matching means evaluating to TRUE). It does not match rows where x is missing. If you really want to match rows with missing x, SQL offers a different syntax `x IS NULL` (and similarly, also `x IS NOT NULL`), Scylla does not yet implement this syntax. In contrast, Cassandra is less consistent in its handling of nulls. The example `x = NULL` is considered an error, not a valid expression whose result is

The rules explained above apply to most expressions, in particular to `WHERE` filters in `SELECT`. However, the evaluation rules for LWT IF clauses (conditional updates) are different: a `IF x = NULL` condition succeeds if `x` is unset. This non-standard behavior of NULLs in IF expressions may be made configurable in a future version. The LWT IF clauses ```cql IF some_map[:var] = 3 ``` or ```cql IF some_map[:var] != 3 ``` is an error if `:var` is `NULL` on Cassandra, but is accepted by Scylla. The result of the comparison, for both `=` and `!=`, is `FALSE`. The LWT IF clauses ```cql IF some_column LIKE :pattern ``` is an error if `:pattern` is `NULL` on Cassandra, but is accepted by Scylla. The result of the pattern match is `FALSE`. REDUCEFUNC extension adds optional reduction function to user-defined aggregate. This allows to speed up aggregation query execution by distributing the calculations to other nodes and reducing partial results into final one. Specification of this function is it has to be scalar function with two arguments, both of the same type as UDA's state, also returning the state type. ```cql CREATE FUNCTION row_fct(acc tuple<bigint, int>, val int) RETURNS NULL ON NULL INPUT RETURNS tuple<bigint, int> LANGUAGE lua AS $$ return { acc[1]+val, acc[2]+1 } $$; CREATE FUNCTION reduce_fct(acc tuple<bigint, int>, acc2 tuple<bigint, int>) RETURNS NULL ON NULL INPUT RETURNS tuple<bigint, int> LANGUAGE lua AS $$ return { acc[1]+acc2[1], acc[2]+acc2[2] } $$; CREATE FUNCTION final_fct(acc tuple<bigint, int>) RETURNS NULL ON NULL INPUT RETURNS double LANGUAGE lua AS $$ return acc[1]/acc[2] $$; CREATE AGGREGATE custom_avg(int) SFUNC row_fct STYPE tuple<bigint, int> REDUCEFUNC reduce_fct FINALFUNC final_fct INITCOND (0, 0); ``` Subscripting a list in a WHERE clause is supported as are maps. ```cql WHERE some_list[:index] = :value ``` The `perpartitionrate_limit` option can be used to limit the allowed rate of requests to each partition in a given table. When the cluster detects that the rate of requests exceeds configured limit, the cluster will start rejecting some of them in order to bring the throughput back to the configured limit. Rejected requests are less costly which can help reduce overload. NOTE: Due to ScyllaDB's distributed nature, tracking per-partition request rates is not perfect and the actual rate of accepted requests may be higher up to a factor of keyspace's `RF`. This feature should not be used to enforce precise limits but rather serve as an overload protection feature. NOTE: This feature works best when shard-aware drivers are used (rejected requests have the least cost). Limits are configured separately for reads and writes. Some examples: ```cql ALTER TABLE t WITH perpartitionrate_limit = { 'maxreadsper_second': 100, 'maxwritesper_second': 200 }; ``` Limit reads only, no limit for writes: ```cql ALTER TABLE t WITH perpartitionrate_limit = { 'maxreadsper_second': 200 }; ``` Rejected requests receive the scylla-specific "Rate limit exceeded" error. If the driver doesn't support it, `Config_error` will be sent instead. For more details, see: Detailed Description of the error Actual values of service level's options may come from different service levels, not only from the one user is assigned with. To facilitate insight into which values come from which service level, there is ``LIST EFFECTIVE SERVICE LEVEL OF <role_name>`` command. ```cql > LIST EFFECTIVE SERVICE LEVEL OF role2; serviceleveloption | effectiveservicelevel | value -+-+- workload_type | sl2 | batch timeout | sl1 | 2s ``` For more details, check