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Posted to commits@cassandra.apache.org by ad...@apache.org on 2022/06/27 14:24:13 UTC
[cassandra] branch cassandra-3.11 updated (34dce0066d -> bc8a260471)
This is an automated email from the ASF dual-hosted git repository.
adelapena pushed a change to branch cassandra-3.11
in repository https://gitbox.apache.org/repos/asf/cassandra.git
from 34dce0066d Merge branch 'cassandra-3.0' into cassandra-3.11
new 09692d5a58 Fix writetime and ttl functions forbidden for collections instead of multicell columns
new bc8a260471 Merge branch 'cassandra-3.0' into cassandra-3.11
The 2 revisions listed above as "new" are entirely new to this
repository and will be described in separate emails. The revisions
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Summary of changes:
CHANGES.txt | 1 +
.../cassandra/pages/cql/cql_singlefile.adoc | 4 +-
doc/modules/cassandra/pages/cql/dml.adoc | 3 +
.../cassandra/cql3/selection/Selectable.java | 8 +-
.../validation/entities/WritetimeOrTTLTest.java | 264 +++++++++++++++++++++
5 files changed, 276 insertions(+), 4 deletions(-)
create mode 100644 test/unit/org/apache/cassandra/cql3/validation/entities/WritetimeOrTTLTest.java
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[cassandra] 01/01: Merge branch 'cassandra-3.0' into cassandra-3.11
Posted by ad...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
adelapena pushed a commit to branch cassandra-3.11
in repository https://gitbox.apache.org/repos/asf/cassandra.git
commit bc8a2604718284b95da52205a9b95b8a69483661
Merge: 34dce0066d 09692d5a58
Author: Andrés de la Peña <a....@gmail.com>
AuthorDate: Mon Jun 27 15:13:45 2022 +0100
Merge branch 'cassandra-3.0' into cassandra-3.11
CHANGES.txt | 1 +
.../cassandra/pages/cql/cql_singlefile.adoc | 4 +-
doc/modules/cassandra/pages/cql/dml.adoc | 3 +
.../cassandra/cql3/selection/Selectable.java | 8 +-
.../validation/entities/WritetimeOrTTLTest.java | 264 +++++++++++++++++++++
5 files changed, 276 insertions(+), 4 deletions(-)
diff --cc CHANGES.txt
index 4d52448919,143dc3864b..cebe5fa7bf
--- a/CHANGES.txt
+++ b/CHANGES.txt
@@@ -1,5 -1,5 +1,6 @@@
-3.0.28
+3.11.14
+Merged from 3.0:
+ * Fix writetime and ttl functions forbidden for collections instead of multicell columns (CASSANDRA-17628)
* Supress CVE-2020-7238 (CASSANDRA-17697)
* Fix issue where frozen maps may not be serialized in the correct order (CASSANDRA-17623)
* Suppress CVE-2022-24823 (CASSANDRA-17633)
diff --cc doc/modules/cassandra/pages/cql/cql_singlefile.adoc
index e2fea00dc0,0000000000..89ed359b73
mode 100644,000000..100644
--- a/doc/modules/cassandra/pages/cql/cql_singlefile.adoc
+++ b/doc/modules/cassandra/pages/cql/cql_singlefile.adoc
@@@ -1,3904 -1,0 +1,3906 @@@
+== Cassandra Query Language (CQL) v3.4.3
+
+\{toc:maxLevel=3}
+
+=== CQL Syntax
+
+==== Preamble
+
+This document describes the Cassandra Query Language (CQL) version 3.
+CQL v3 is not backward compatible with CQL v2 and differs from it in
+numerous ways. Note that this document describes the last version of the
+languages. However, the link:#changes[changes] section provides the diff
+between the different versions of CQL v3.
+
+CQL v3 offers a model very close to SQL in the sense that data is put in
+_tables_ containing _rows_ of _columns_. For that reason, when used in
+this document, these terms (tables, rows and columns) have the same
+definition than they have in SQL. But please note that as such, they do
+*not* refer to the concept of rows and columns found in the internal
+implementation of Cassandra and in the thrift and CQL v2 API.
+
+==== Conventions
+
+To aid in specifying the CQL syntax, we will use the following
+conventions in this document:
+
+* Language rules will be given in a
+http://en.wikipedia.org/wiki/Backus%E2%80%93Naur_Form[BNF] -like
+notation:
+
+bc(syntax). ::= TERMINAL
+
+* Nonterminal symbols will have `<angle brackets>`.
+* As additional shortcut notations to BNF, we’ll use traditional regular
+expression’s symbols (`?`, `+` and `*`) to signify that a given symbol
+is optional and/or can be repeated. We’ll also allow parentheses to
+group symbols and the `[<characters>]` notation to represent any one of
+`<characters>`.
+* The grammar is provided for documentation purposes and leave some
+minor details out. For instance, the last column definition in a
+`CREATE TABLE` statement is optional but supported if present even
+though the provided grammar in this document suggest it is not
+supported.
+* Sample code will be provided in a code block:
+
+bc(sample). SELECT sample_usage FROM cql;
+
+* References to keywords or pieces of CQL code in running text will be
+shown in a `fixed-width font`.
+
+[[identifiers]]
+==== Identifiers and keywords
+
+The CQL language uses _identifiers_ (or _names_) to identify tables,
+columns and other objects. An identifier is a token matching the regular
+expression `[a-zA-Z]``[a-zA-Z0-9_]``*`.
+
+A number of such identifiers, like `SELECT` or `WITH`, are _keywords_.
+They have a fixed meaning for the language and most are reserved. The
+list of those keywords can be found in link:#appendixA[Appendix A].
+
+Identifiers and (unquoted) keywords are case insensitive. Thus `SELECT`
+is the same than `select` or `sElEcT`, and `myId` is the same than
+`myid` or `MYID` for instance. A convention often used (in particular by
+the samples of this documentation) is to use upper case for keywords and
+lower case for other identifiers.
+
+There is a second kind of identifiers called _quoted identifiers_
+defined by enclosing an arbitrary sequence of characters in
+double-quotes(`"`). Quoted identifiers are never keywords. Thus
+`"select"` is not a reserved keyword and can be used to refer to a
+column, while `select` would raise a parse error. Also, contrarily to
+unquoted identifiers and keywords, quoted identifiers are case sensitive
+(`"My Quoted Id"` is _different_ from `"my quoted id"`). A fully
+lowercase quoted identifier that matches `[a-zA-Z]``[a-zA-Z0-9_]``*` is
+equivalent to the unquoted identifier obtained by removing the
+double-quote (so `"myid"` is equivalent to `myid` and to `myId` but
+different from `"myId"`). Inside a quoted identifier, the double-quote
+character can be repeated to escape it, so `"foo "" bar"` is a valid
+identifier.
+
+*Warning*: _quoted identifiers_ allows to declare columns with arbitrary
+names, and those can sometime clash with specific names used by the
+server. For instance, when using conditional update, the server will
+respond with a result-set containing a special result named
+`"[applied]"`. If you’ve declared a column with such a name, this could
+potentially confuse some tools and should be avoided. In general,
+unquoted identifiers should be preferred but if you use quoted
+identifiers, it is strongly advised to avoid any name enclosed by
+squared brackets (like `"[applied]"`) and any name that looks like a
+function call (like `"f(x)"`).
+
+==== Constants
+
+CQL defines the following kind of _constants_: strings, integers,
+floats, booleans, uuids and blobs:
+
+* A string constant is an arbitrary sequence of characters characters
+enclosed by single-quote(`'`). One can include a single-quote in a
+string by repeating it, e.g. `'It''s raining today'`. Those are not to
+be confused with quoted identifiers that use double-quotes.
+* An integer constant is defined by `'-'?[0-9]+`.
+* A float constant is defined by
+`'-'?[0-9]+('.'[0-9]*)?([eE][+-]?[0-9+])?`. On top of that, `NaN` and
+`Infinity` are also float constants.
+* A boolean constant is either `true` or `false` up to
+case-insensitivity (i.e. `True` is a valid boolean constant).
+* A http://en.wikipedia.org/wiki/Universally_unique_identifier[UUID]
+constant is defined by `hex{8}-hex{4}-hex{4}-hex{4}-hex{12}` where `hex`
+is an hexadecimal character, e.g. `[0-9a-fA-F]` and `{4}` is the number
+of such characters.
+* A blob constant is an hexadecimal number defined by `0[xX](hex)+`
+where `hex` is an hexadecimal character, e.g. `[0-9a-fA-F]`.
+
+For how these constants are typed, see the link:#types[data types
+section].
+
+==== Comments
+
+A comment in CQL is a line beginning by either double dashes (`--`) or
+double slash (`//`).
+
+Multi-line comments are also supported through enclosure within `/*` and
+`*/` (but nesting is not supported).
+
+bc(sample). +
+— This is a comment +
+// This is a comment too +
+/* This is +
+a multi-line comment */
+
+==== Statements
+
+CQL consists of statements. As in SQL, these statements can be divided
+in 3 categories:
+
+* Data definition statements, that allow to set and change the way data
+is stored.
+* Data manipulation statements, that allow to change data
+* Queries, to look up data
+
+All statements end with a semicolon (`;`) but that semicolon can be
+omitted when dealing with a single statement. The supported statements
+are described in the following sections. When describing the grammar of
+said statements, we will reuse the non-terminal symbols defined below:
+
+bc(syntax).. +
+::= any quoted or unquoted identifier, excluding reserved keywords +
+::= ( `.')?
+
+::= a string constant +
+::= an integer constant +
+::= a float constant +
+::= | +
+::= a uuid constant +
+::= a boolean constant +
+::= a blob constant
+
+::= +
+| +
+| +
+| +
+| +
+::= `?' +
+| `:' +
+::= +
+| +
+| +
+| `(' ( (`,' )*)? `)'
+
+::= +
+| +
+| +
+::= `\{' ( `:' ( `,' `:' )* )? `}' +
+::= `\{' ( ( `,' )* )? `}' +
+::= `[' ( ( `,' )* )? `]'
+
+::=
+
+::= (AND )* +
+::= `=' ( | | ) +
+p. +
+Please note that not every possible productions of the grammar above
+will be valid in practice. Most notably, `<variable>` and nested
+`<collection-literal>` are currently not allowed inside
+`<collection-literal>`.
+
+A `<variable>` can be either anonymous (a question mark (`?`)) or named
+(an identifier preceded by `:`). Both declare a bind variables for
+link:#preparedStatement[prepared statements]. The only difference
+between an anymous and a named variable is that a named one will be
+easier to refer to (how exactly depends on the client driver used).
+
+The `<properties>` production is use by statement that create and alter
+keyspaces and tables. Each `<property>` is either a _simple_ one, in
+which case it just has a value, or a _map_ one, in which case it’s value
+is a map grouping sub-options. The following will refer to one or the
+other as the _kind_ (_simple_ or _map_) of the property.
+
+A `<tablename>` will be used to identify a table. This is an identifier
+representing the table name that can be preceded by a keyspace name. The
+keyspace name, if provided, allow to identify a table in another
+keyspace than the currently active one (the currently active keyspace is
+set through the `USE` statement).
+
+For supported `<function>`, see the section on
+link:#functions[functions].
+
+Strings can be either enclosed with single quotes or two dollar
+characters. The second syntax has been introduced to allow strings that
+contain single quotes. Typical candidates for such strings are source
+code fragments for user-defined functions.
+
+_Sample:_
+
+bc(sample).. +
+`some string value'
+
+$$double-dollar string can contain single ’ quotes$$ +
+p.
+
+[[preparedStatement]]
+==== Prepared Statement
+
+CQL supports _prepared statements_. Prepared statement is an
+optimization that allows to parse a query only once but execute it
+multiple times with different concrete values.
+
+In a statement, each time a column value is expected (in the data
+manipulation and query statements), a `<variable>` (see above) can be
+used instead. A statement with bind variables must then be _prepared_.
+Once it has been prepared, it can executed by providing concrete values
+for the bind variables. The exact procedure to prepare a statement and
+execute a prepared statement depends on the CQL driver used and is
+beyond the scope of this document.
+
+In addition to providing column values, bind markers may be used to
+provide values for `LIMIT`, `TIMESTAMP`, and `TTL` clauses. If anonymous
+bind markers are used, the names for the query parameters will be
+`[limit]`, `[timestamp]`, and `[ttl]`, respectively.
+
+[[dataDefinition]]
+=== Data Definition
+
+[[createKeyspaceStmt]]
+==== CREATE KEYSPACE
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE KEYSPACE (IF NOT EXISTS)? WITH +
+p. +
+_Sample:_
+
+bc(sample).. +
+CREATE KEYSPACE Excelsior +
+WITH replication = \{’class’: `SimpleStrategy', `replication_factor' :
+3};
+
+CREATE KEYSPACE Excalibur +
+WITH replication = \{’class’: `NetworkTopologyStrategy', `DC1' : 1,
+`DC2' : 3} +
+AND durable_writes = false; +
+p. +
+The `CREATE KEYSPACE` statement creates a new top-level _keyspace_. A
+keyspace is a namespace that defines a replication strategy and some
+options for a set of tables. Valid keyspaces names are identifiers
+composed exclusively of alphanumerical characters and whose length is
+lesser or equal to 32. Note that as identifiers, keyspace names are case
+insensitive: use a quoted identifier for case sensitive keyspace names.
+
+The supported `<properties>` for `CREATE KEYSPACE` are:
+
+[cols=",,,,",options="header",]
+|===
+|name |kind |mandatory |default |description
+|`replication` |_map_ |yes | |The replication strategy and options to
+use for the keyspace.
+
+|`durable_writes` |_simple_ |no |true |Whether to use the commit log for
+updates on this keyspace (disable this option at your own risk!).
+|===
+
+The `replication` `<property>` is mandatory. It must at least contains
+the `'class'` sub-option which defines the replication strategy class to
+use. The rest of the sub-options depends on that replication strategy
+class. By default, Cassandra support the following `'class'`:
+
+* `'SimpleStrategy'`: A simple strategy that defines a simple
+replication factor for the whole cluster. The only sub-options supported
+is `'replication_factor'` to define that replication factor and is
+mandatory.
+* `'NetworkTopologyStrategy'`: A 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 each time the key is the name
+of a datacenter and the value the replication factor for that
+data-center.
+
+Attempting to create an already existing keyspace will return an error
+unless the `IF NOT EXISTS` option is used. If it is used, the statement
+will be a no-op if the keyspace already exists.
+
+[[useStmt]]
+==== USE
+
+_Syntax:_
+
+bc(syntax). ::= USE
+
+_Sample:_
+
+bc(sample). USE myApp;
+
+The `USE` statement takes an existing keyspace name as argument and set
+it as the per-connection current working keyspace. All subsequent
+keyspace-specific actions will be performed in the context of the
+selected keyspace, unless link:#statements[otherwise specified], until
+another USE statement is issued or the connection terminates.
+
+[[alterKeyspaceStmt]]
+==== ALTER KEYSPACE
+
+_Syntax:_
+
+bc(syntax).. +
+::= ALTER KEYSPACE WITH +
+p. +
+_Sample:_
+
+bc(sample).. +
+ALTER KEYSPACE Excelsior +
+WITH replication = \{’class’: `SimpleStrategy', `replication_factor' :
+4};
+
+The `ALTER KEYSPACE` statement alters the properties of an existing
+keyspace. The supported `<properties>` are the same as for the
+link:#createKeyspaceStmt[`CREATE KEYSPACE`] statement.
+
+[[dropKeyspaceStmt]]
+==== DROP KEYSPACE
+
+_Syntax:_
+
+bc(syntax). ::= DROP KEYSPACE ( IF EXISTS )?
+
+_Sample:_
+
+bc(sample). DROP KEYSPACE myApp;
+
+A `DROP KEYSPACE` statement results in the immediate, irreversible
+removal of an existing keyspace, including all column families in it,
+and all data contained in those column families.
+
+If the keyspace does not exists, the statement will return an error,
+unless `IF EXISTS` is used in which case the operation is a no-op.
+
+[[createTableStmt]]
+==== CREATE TABLE
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE ( TABLE | COLUMNFAMILY ) ( IF NOT EXISTS )? +
+`(' ( `,' )* `)' +
+( WITH ( AND )* )?
+
+::= ( STATIC )? ( PRIMARY KEY )? +
+| PRIMARY KEY `(' ( `,' )* `)'
+
+::= +
+| `(' (`,' )* `)'
+
+::= +
+| COMPACT STORAGE +
+| CLUSTERING ORDER +
+p. +
+_Sample:_
+
+bc(sample).. +
+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' }; +
+p. +
+The `CREATE TABLE` statement creates a new table. Each such table is a
+set of _rows_ (usually representing related entities) for which it
+defines a number of properties. A table is defined by a
+link:#createTableName[name], it defines the columns composing rows of
+the table and have a number of link:#createTableOptions[options]. Note
+that the `CREATE COLUMNFAMILY` syntax is supported as an alias for
+`CREATE TABLE` (for historical reasons).
+
+Attempting to create an already existing table will return an error
+unless the `IF NOT EXISTS` option is used. If it is used, the statement
+will be a no-op if the table already exists.
+
+[[createTableName]]
+===== `<tablename>`
+
+Valid table names are the same as valid
+link:#createKeyspaceStmt[keyspace names] (up to 32 characters long
+alphanumerical identifiers). If the table name is provided alone, the
+table is created within the current keyspace (see `USE`), but if it is
+prefixed by an existing keyspace name (see
+link:#statements[`<tablename>`] grammar), it is created in the specified
+keyspace (but does *not* change the current keyspace).
+
+[[createTableColumn]]
+===== `<column-definition>`
+
+A `CREATE TABLE` statement defines the columns that rows of the table
+can have. A _column_ is defined by its name (an identifier) and its type
+(see the link:#types[data types] section for more details on allowed
+types and their properties).
+
+Within a table, a row is uniquely identified by its `PRIMARY KEY` (or
+more simply the key), and hence all table definitions *must* define a
+PRIMARY KEY (and only one). A `PRIMARY KEY` is composed of one or more
+of the columns defined in the table. If the `PRIMARY KEY` is only one
+column, this can be specified directly after the column definition.
+Otherwise, it must be specified by following `PRIMARY KEY` by the
+comma-separated list of column names composing the key within
+parenthesis. Note that:
+
+bc(sample). +
+CREATE TABLE t ( +
+k int PRIMARY KEY, +
+other text +
+)
+
+is equivalent to
+
+bc(sample). +
+CREATE TABLE t ( +
+k int, +
+other text, +
+PRIMARY KEY (k) +
+)
+
+[[createTablepartitionClustering]]
+===== Partition key and clustering columns
+
+In CQL, the order in which columns are defined for the `PRIMARY KEY`
+matters. The first column of the key is called the _partition key_. It
+has the property that all the rows sharing the same partition key (even
+across table in fact) are stored on the same physical node. Also,
+insertion/update/deletion on rows sharing the same partition key for a
+given table are performed _atomically_ and in _isolation_. Note that it
+is possible to have a composite partition key, i.e. a partition key
+formed of multiple columns, using an extra set of parentheses to define
+which columns forms the partition key.
+
+The remaining columns of the `PRIMARY KEY` definition, if any, are
+called __clustering columns. On a given physical node, rows for a given
+partition key are stored in the order induced by the clustering columns,
+making the retrieval of rows in that clustering order particularly
+efficient (see `SELECT`).
+
+[[createTableStatic]]
+===== `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, in:
+
+bc(sample). +
+CREATE TABLE test ( +
+pk int, +
+t int, +
+v text, +
+s text static, +
+PRIMARY KEY (pk, t) +
+); +
+INSERT INTO test(pk, t, v, s) VALUES (0, 0, `val0', `static0'); +
+INSERT INTO test(pk, t, v, s) VALUES (0, 1, `val1', `static1'); +
+SELECT * FROM test WHERE pk=0 AND t=0;
+
+the last query will return `'static1'` as value for `s`, since `s` is
+static and thus the 2nd insertion modified this ``shared'' value. Note
+however that static columns are only static within a given partition,
+and if in the example above both rows where from different partitions
+(i.e. if they had different value for `pk`), then the 2nd insertion
+would not have modified the value of `s` for the first row.
+
+A few restrictions applies to when static columns are allowed:
+
+* tables with the `COMPACT STORAGE` option (see below) cannot have 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
+
+[[createTableOptions]]
+===== `<option>`
+
+The `CREATE TABLE` statement supports a number of options that controls
+the configuration of a new table. These options can be specified after
+the `WITH` keyword.
+
+The first of these option is `COMPACT STORAGE`. This option is mainly
+targeted towards backward compatibility for definitions created before
+CQL3 (see
+http://www.datastax.com/dev/blog/thrift-to-cql3[www.datastax.com/dev/blog/thrift-to-cql3]
+for more details). The option also provides a slightly more compact
+layout of data on disk but at the price of diminished flexibility and
+extensibility for the table. Most notably, `COMPACT STORAGE` tables
+cannot have collections nor static columns and a `COMPACT STORAGE` table
+with at least one clustering column supports exactly one (as in not 0
+nor more than 1) column not part of the `PRIMARY KEY` definition (which
+imply in particular that you cannot add nor remove columns after
+creation). For those reasons, `COMPACT STORAGE` is not recommended
+outside of the backward compatibility reason evoked above.
+
+Another option is `CLUSTERING ORDER`. It allows to define the ordering
+of rows on disk. It takes the list of the clustering column names with,
+for each of them, the on-disk order (Ascending or descending). Note that
+this option affects link:#selectOrderBy[what `ORDER BY` are allowed
+during `SELECT`].
+
+Table creation supports the following other `<property>`:
+
+[cols=",,,",options="header",]
+|===
+|option |kind |default |description
+|`comment` |_simple_ |none |A free-form, human-readable comment.
+
+|`gc_grace_seconds` |_simple_ |864000 |Time to wait before garbage
+collecting tombstones (deletion markers).
+
+|`bloom_filter_fp_chance` |_simple_ |0.00075 |The target probability of
+false positive of the sstable bloom filters. Said 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, see
+link:#compactionOptions[below].
+
+|`compression` |_map_ |_see below_ |Compression options, see
+link:#compressionOptions[below].
+
+|`caching` |_map_ |_see below_ |Caching options, see
+link:#cachingOptions[below].
+|===
+
+[[compactionOptions]]
+===== Compaction options
+
+The `compaction` property must at least define the `'class'` sub-option,
+that defines the compaction strategy class to use. The default supported
+class are `'SizeTieredCompactionStrategy'`,
+`'LeveledCompactionStrategy'`, `'DateTieredCompactionStrategy'` and
+`'TimeWindowCompactionStrategy'`. Custom strategy can be provided by
+specifying the full class name as a link:#constants[string constant].
+The rest of the sub-options depends on the chosen class. The sub-options
+supported by the default classes are:
+
+[cols=",,,",options="header",]
+|===
+|option |supported compaction strategy |default |description
+|`enabled` |_all_ |true |A boolean denoting whether compaction should be
+enabled or not.
+
+|`tombstone_threshold` |_all_ |0.2 |A ratio such that if a sstable has
+more than this ratio of gcable tombstones over all contained columns,
+the sstable will be compacted (with no other sstables) for the purpose
+of purging those tombstones.
+
+|`tombstone_compaction_interval` |_all_ |1 day |The minimum time to wait
+after an sstable creation time before considering it for ``tombstone
+compaction'', where ``tombstone compaction'' is the compaction triggered
+if the sstable has more gcable tombstones than `tombstone_threshold`.
+
+|`unchecked_tombstone_compaction` |_all_ |false |Setting this to true
+enables more aggressive tombstone compactions - single sstable tombstone
+compactions will run without checking how likely it is that they will be
+successful.
+
+|`min_sstable_size` |SizeTieredCompactionStrategy |50MB |The size tiered
+strategy groups SSTables to compact in buckets. A bucket groups SSTables
+that differs from less than 50% in size. However, for small sizes, this
+would result in a bucketing that is too fine grained. `min_sstable_size`
+defines a size threshold (in bytes) below which all SSTables belong to
+one unique bucket
+
+|`min_threshold` |SizeTieredCompactionStrategy |4 |Minimum number of
+SSTables needed to start a minor compaction.
+
+|`max_threshold` |SizeTieredCompactionStrategy |32 |Maximum number of
+SSTables processed by one minor compaction.
+
+|`bucket_low` |SizeTieredCompactionStrategy |0.5 |Size tiered consider
+sstables to be within the same bucket if their size is within
+[average_size * `bucket_low`, average_size * `bucket_high` ] (i.e the
+default groups sstable whose sizes diverges by at most 50%)
+
+|`bucket_high` |SizeTieredCompactionStrategy |1.5 |Size tiered consider
+sstables to be within the same bucket if their size is within
+[average_size * `bucket_low`, average_size * `bucket_high` ] (i.e the
+default groups sstable whose sizes diverges by at most 50%).
+
+|`sstable_size_in_mb` |LeveledCompactionStrategy |5MB |The target size
+(in MB) for sstables in the leveled strategy. Note that while sstable
+sizes should stay less or equal to `sstable_size_in_mb`, it is possible
+to exceptionally have a larger sstable as during compaction, data for a
+given partition key are never split into 2 sstables
+
+|`timestamp_resolution` |DateTieredCompactionStrategy |MICROSECONDS |The
+timestamp resolution used when inserting data, could be MILLISECONDS,
+MICROSECONDS etc (should be understandable by Java TimeUnit) - don’t
+change this unless you do mutations with USING TIMESTAMP (or equivalent
+directly in the client)
+
+|`base_time_seconds` |DateTieredCompactionStrategy |60 |The base size of
+the time windows.
+
+|`max_sstable_age_days` |DateTieredCompactionStrategy |365 |SSTables
+only containing data that is older than this will never be compacted.
+
+|`timestamp_resolution` |TimeWindowCompactionStrategy |MICROSECONDS |The
+timestamp resolution used when inserting data, could be MILLISECONDS,
+MICROSECONDS etc (should be understandable by Java TimeUnit) - don’t
+change this unless you do mutations with USING TIMESTAMP (or equivalent
+directly in the client)
+
+|`compaction_window_unit` |TimeWindowCompactionStrategy |DAYS |The Java
+TimeUnit used for the window size, set in conjunction with
+`compaction_window_size`. Must be one of DAYS, HOURS, MINUTES
+
+|`compaction_window_size` |TimeWindowCompactionStrategy |1 |The number
+of `compaction_window_unit` units that make up a time window.
+
+|`unsafe_aggressive_sstable_expiration` |TimeWindowCompactionStrategy
+|false |Expired sstables will be dropped without checking its data is
+shadowing other sstables. This is a potentially risky option that can
+lead to data loss or deleted data re-appearing, going beyond what
+`unchecked_tombstone_compaction` does for single sstable compaction. Due
+to the risk the jvm must also be started with
+`-Dcassandra.unsafe_aggressive_sstable_expiration=true`.
+|===
+
+[[compressionOptions]]
+===== Compression options
+
+For the `compression` property, the following sub-options are available:
+
+[cols=",,,,,",options="header",]
+|===
+|option |default |description | | |
+|`class` |LZ4Compressor |The compression algorithm to use. Default
+compressor are: LZ4Compressor, SnappyCompressor and DeflateCompressor.
+Use `'enabled' : false` to disable compression. Custom compressor can be
+provided by specifying the full class name as a link:#constants[string
+constant]. | | |
+
+|`enabled` |true |By default compression is enabled. To disable it, set
+`enabled` to `false` |`chunk_length_in_kb` |64KB |On disk SSTables are
+compressed by block (to allow random reads). This defines the size (in
+KB) of said block. Bigger values may improve the compression rate, but
+increases the minimum size of data to be read from disk for a read
+
+|`crc_check_chance` |1.0 |When compression is enabled, each compressed
+block includes a checksum of that block for the purpose of detecting
+disk bitrot and avoiding the propagation of corruption to other replica.
+This option defines the probability with which those checksums are
+checked during read. By default they are always checked. Set to 0 to
+disable checksum checking and to 0.5 for instance to check them every
+other read | | |
+|===
+
+[[cachingOptions]]
+===== Caching options
+
+For the `caching` property, the following sub-options are available:
+
+[cols=",,",options="header",]
+|===
+|option |default |description
+|`keys` |ALL |Whether to cache keys (``key cache'') for this table.
+Valid values are: `ALL` and `NONE`.
+
+|`rows_per_partition` |NONE |The amount of rows to cache per partition
+(``row cache''). If an integer `n` is specified, the first `n` queried
+rows of a partition will be cached. Other possible options are `ALL`, to
+cache all rows of a queried partition, or `NONE` to disable row caching.
+|===
+
+===== Other considerations:
+
+* When link:#insertStmt[inserting] / link:#updateStmt[updating] a given
+row, not all columns needs to be defined (except for those part of the
+key), and missing columns occupy no space on disk. Furthermore, adding
+new columns (see `ALTER TABLE`) is a constant time operation. There is
+thus no need to try to anticipate future usage (or to cry when you
+haven’t) when creating a table.
+
+[[alterTableStmt]]
+==== ALTER TABLE
+
+_Syntax:_
+
+bc(syntax).. +
+::= ALTER (TABLE | COLUMNFAMILY)
+
+::= ADD +
+| ADD ( ( , )* ) +
+| DROP +
+| DROP ( ( , )* ) +
+| WITH ( AND )* +
+p. +
+_Sample:_
+
+bc(sample).. +
+ALTER TABLE addamsFamily
+
+ALTER TABLE addamsFamily +
+ADD gravesite varchar;
+
+ALTER TABLE addamsFamily +
+WITH comment = `A most excellent and useful column family'; +
+p. +
+The `ALTER` statement is used to manipulate table definitions. It allows
+for adding new columns, dropping existing ones, or updating the table
+options. As with table creation, `ALTER COLUMNFAMILY` is allowed as an
+alias for `ALTER TABLE`.
+
+The `<tablename>` is the table name optionally preceded by the keyspace
+name. The `<instruction>` defines the alteration to perform:
+
+* `ADD`: Adds a new column to the table. The `<identifier>` for the new
+column must not conflict with an existing column. Moreover, columns
+cannot be added to tables defined with the `COMPACT STORAGE` option.
+* `DROP`: Removes a column from the table. Dropped columns will
+immediately become unavailable in the queries and will not be included
+in compacted sstables in the future. If a column is readded, queries
+won’t return values written before the column was last dropped. It is
+assumed that timestamps represent actual time, so if this is not your
+case, you should NOT readd previously dropped columns. Columns can’t be
+dropped from tables defined with the `COMPACT STORAGE` option.
+* `WITH`: Allows to update the options of the table. The
+link:#createTableOptions[supported `<option>`] (and syntax) are the same
+as for the `CREATE TABLE` statement except that `COMPACT STORAGE` is not
+supported. 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.
+
+===== CQL type compatibility:
+
+CQL data types may be converted only as the following table.
+
+[cols=",",options="header",]
+|===
+|Data type may be altered to: |Data type
+|timestamp |bigint
+
+|ascii, bigint, boolean, date, decimal, double, float, inet, int,
+smallint, text, time, timestamp, timeuuid, tinyint, uuid, varchar,
+varint |blob
+
+|int |date
+
+|ascii, varchar |text
+
+|bigint |time
+
+|bigint |timestamp
+
+|timeuuid |uuid
+
+|ascii, text |varchar
+
+|bigint, int, timestamp |varint
+|===
+
+Clustering columns have stricter requirements, only the below
+conversions are allowed.
+
+[cols=",",options="header",]
+|===
+|Data type may be altered to: |Data type
+|ascii, text, varchar |blob
+|ascii, varchar |text
+|ascii, text |varchar
+|===
+
+[[dropTableStmt]]
+==== DROP TABLE
+
+_Syntax:_
+
+bc(syntax). ::= DROP TABLE ( IF EXISTS )?
+
+_Sample:_
+
+bc(sample). DROP TABLE worldSeriesAttendees;
+
+The `DROP TABLE` statement results in the immediate, irreversible
+removal of a table, including all data contained in it. As for table
+creation, `DROP COLUMNFAMILY` is allowed as an alias for `DROP TABLE`.
+
+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.
+
+[[truncateStmt]]
+==== TRUNCATE
+
+_Syntax:_
+
+bc(syntax). ::= TRUNCATE ( TABLE | COLUMNFAMILY )?
+
+_Sample:_
+
+bc(sample). TRUNCATE superImportantData;
+
+The `TRUNCATE` statement permanently removes all data from a table.
+
+[[createIndexStmt]]
+==== CREATE INDEX
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE ( CUSTOM )? INDEX ( IF NOT EXISTS )? ( )? +
+ON `(' `)' +
+( USING ( WITH OPTIONS = )? )?
+
+::= +
+| keys( ) +
+p. +
+_Sample:_
+
+bc(sample). +
+CREATE INDEX userIndex ON NerdMovies (user); +
+CREATE INDEX ON Mutants (abilityId); +
+CREATE INDEX ON users (keys(favs)); +
+CREATE CUSTOM INDEX ON users (email) USING `path.to.the.IndexClass'; +
+CREATE CUSTOM INDEX ON users (email) USING `path.to.the.IndexClass' WITH
+OPTIONS = \{’storage’: `/mnt/ssd/indexes/'};
+
+The `CREATE INDEX` statement is used to create a new (automatic)
+secondary index for a given (existing) column in a given table. A name
+for the index itself can be specified before the `ON` keyword, if
+desired. If data already exists for the column, it will be indexed
+asynchronously. After the index is created, new data for the column is
+indexed automatically at insertion time.
+
+Attempting to create an already existing index will return an error
+unless the `IF NOT EXISTS` option is used. If it is used, the statement
+will be a no-op if the index already exists.
+
+[[keysIndex]]
+===== Indexes on Map Keys
+
+When creating an index on a link:#map[map column], you may index either
+the keys or the values. If the column identifier is placed within the
+`keys()` function, the index will be on the map keys, allowing you to
+use `CONTAINS KEY` in `WHERE` clauses. Otherwise, the index will be on
+the map values.
+
+[[dropIndexStmt]]
+==== DROP INDEX
+
+_Syntax:_
+
+bc(syntax). ::= DROP INDEX ( IF EXISTS )? ( `.' )?
+
+_Sample:_
+
+bc(sample).. +
+DROP INDEX userIndex;
+
+DROP INDEX userkeyspace.address_index; +
+p. +
+The `DROP INDEX` statement is used to drop an existing secondary index.
+The argument of the statement is the index name, which may optionally
+specify the keyspace of the index.
+
+If the index does not exists, the statement will return an error, unless
+`IF EXISTS` is used in which case the operation is a no-op.
+
+[[createMVStmt]]
+==== CREATE MATERIALIZED VIEW
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE MATERIALIZED VIEW ( IF NOT EXISTS )? AS +
+SELECT ( `(' ( `,' ) * `)' | `*' ) +
+FROM +
+( WHERE )? +
+PRIMARY KEY `(' ( `,' )* `)' +
+( WITH ( AND )* )? +
+p. +
+_Sample:_
+
+bc(sample).. +
+CREATE MATERIALIZED VIEW monkeySpecies_by_population AS +
+SELECT * +
+FROM monkeySpecies +
+WHERE population IS NOT NULL AND species IS NOT NULL +
+PRIMARY KEY (population, species) +
+WITH comment=`Allow query by population instead of species'; +
+p. +
+The `CREATE MATERIALIZED VIEW` statement creates a new materialized
+view. Each such view is a set of _rows_ which corresponds to rows which
+are present in the underlying, or base, table specified in the `SELECT`
+statement. A materialized view cannot be directly updated, but updates
+to the base table will cause corresponding updates in the view.
+
+Attempting to create an already existing materialized view will return
+an error unless the `IF NOT EXISTS` option is used. If it is used, the
+statement will be a no-op if the materialized view already exists.
+
+[[createMVWhere]]
+===== `WHERE` Clause
+
+The `<where-clause>` is similar to the link:#selectWhere[where clause of
+a `SELECT` statement], with a few differences. First, the where clause
+must contain an expression that disallows `NULL` values in columns in
+the view’s primary key. If no other restriction is desired, this can be
+accomplished with an `IS NOT NULL` expression. Second, only columns
+which are in the base table’s primary key may be restricted with
+expressions other than `IS NOT NULL`. (Note that this second restriction
+may be lifted in the future.)
+
+[[alterMVStmt]]
+==== ALTER MATERIALIZED VIEW
+
+_Syntax:_
+
+bc(syntax). ::= ALTER MATERIALIZED VIEW +
+WITH ( AND )*
+
+The `ALTER MATERIALIZED VIEW` statement allows options to be update;
+these options are the same as `CREATE TABLE`’s options.
+
+[[dropMVStmt]]
+==== DROP MATERIALIZED VIEW
+
+_Syntax:_
+
+bc(syntax). ::= DROP MATERIALIZED VIEW ( IF EXISTS )?
+
+_Sample:_
+
+bc(sample). DROP MATERIALIZED VIEW monkeySpecies_by_population;
+
+The `DROP MATERIALIZED VIEW` statement is used to drop an existing
+materialized view.
+
+If the materialized view does not exists, the statement will return an
+error, unless `IF EXISTS` is used in which case the operation is a
+no-op.
+
+[[createTypeStmt]]
+==== CREATE TYPE
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE TYPE ( IF NOT EXISTS )? +
+`(' ( `,' )* `)'
+
+::= ( `.' )?
+
+::=
+
+_Sample:_
+
+bc(sample).. +
+CREATE TYPE address ( +
+street_name text, +
+street_number int, +
+city text, +
+state text, +
+zip int +
+)
+
+CREATE TYPE work_and_home_addresses ( +
+home_address address, +
+work_address address +
+) +
+p. +
+The `CREATE TYPE` statement creates a new user-defined type. Each type
+is a set of named, typed fields. Field types may be any valid type,
+including collections and other existing user-defined types.
+
+Attempting to create an already existing type will result in an error
+unless the `IF NOT EXISTS` option is used. If it is used, the statement
+will be a no-op if the type already exists.
+
+[[createTypeName]]
+===== `<typename>`
+
+Valid type names are identifiers. The names of existing CQL types and
+link:#appendixB[reserved type names] may not be used.
+
+If the type name is provided alone, the type is created with the current
+keyspace (see `USE`). If it is prefixed by an existing keyspace name,
+the type is created within the specified keyspace instead of the current
+keyspace.
+
+[[alterTypeStmt]]
+==== ALTER TYPE
+
+_Syntax:_
+
+bc(syntax).. +
+::= ALTER TYPE
+
+::= ADD +
+| RENAME TO ( AND TO )* +
+p. +
+_Sample:_
+
+bc(sample).. +
+ALTER TYPE address ADD country text
+
+ALTER TYPE address RENAME zip TO zipcode AND street_name TO street +
+p. +
+The `ALTER TYPE` statement is used to manipulate type definitions. It
+allows for adding new fields, renaming existing fields, or changing the
+type of existing fields.
+
+[[dropTypeStmt]]
+==== DROP TYPE
+
+_Syntax:_
+
+bc(syntax).. +
+::= DROP TYPE ( IF EXISTS )? +
+p. +
+The `DROP TYPE` statement results in the immediate, irreversible removal
+of a type. Attempting to drop a type that is still in use by another
+type or a table will result in an error.
+
+If the type does not exist, an error will be returned unless `IF EXISTS`
+is used, in which case the operation is a no-op.
+
+[[createTriggerStmt]]
+==== CREATE TRIGGER
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE TRIGGER ( IF NOT EXISTS )? ( )? +
+ON +
+USING
+
+_Sample:_
+
+bc(sample). +
+CREATE TRIGGER myTrigger ON myTable USING
+`org.apache.cassandra.triggers.InvertedIndex';
+
+The actual logic that makes up the trigger can be written in any Java
+(JVM) language and exists outside the database. You place the trigger
+code in a `lib/triggers` subdirectory of the Cassandra installation
+directory, it loads during cluster startup, and exists on every node
+that participates in a cluster. The trigger defined on a table fires
+before a requested DML statement occurs, which ensures the atomicity of
+the transaction.
+
+[[dropTriggerStmt]]
+==== DROP TRIGGER
+
+_Syntax:_
+
+bc(syntax).. +
+::= DROP TRIGGER ( IF EXISTS )? ( )? +
+ON +
+p. +
+_Sample:_
+
+bc(sample). +
+DROP TRIGGER myTrigger ON myTable;
+
+`DROP TRIGGER` statement removes the registration of a trigger created
+using `CREATE TRIGGER`.
+
+[[createFunctionStmt]]
+==== CREATE FUNCTION
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE ( OR REPLACE )? +
+FUNCTION ( IF NOT EXISTS )? +
+( `.' )? +
+`(' ( `,' )* `)' +
+( CALLED | RETURNS NULL ) ON NULL INPUT +
+RETURNS +
+LANGUAGE +
+AS
+
+_Sample:_
+
+bc(sample). +
+CREATE OR REPLACE FUNCTION somefunction +
+( somearg int, anotherarg text, complexarg frozen, listarg list ) +
+RETURNS NULL ON NULL INPUT +
+RETURNS text +
+LANGUAGE java +
+AS $$ +
+// some Java code +
+$$; +
+CREATE FUNCTION akeyspace.fname IF NOT EXISTS +
+( someArg int ) +
+CALLED ON NULL INPUT +
+RETURNS text +
+LANGUAGE java +
+AS $$ +
+// some Java code +
+$$;
+
+`CREATE FUNCTION` creates or replaces a user-defined function.
+
+[[functionSignature]]
+===== Function Signature
+
+Signatures are used to distinguish individual functions. The signature
+consists of:
+
+. The fully qualified function name - i.e _keyspace_ plus
+_function-name_
+. The concatenated list of all argument types
+
+Note that keyspace names, function names and argument types are subject
+to the default naming conventions and case-sensitivity rules.
+
+`CREATE FUNCTION` with the optional `OR REPLACE` keywords either creates
+a function or replaces an existing one with the same signature. A
+`CREATE FUNCTION` without `OR REPLACE` fails if a function with the same
+signature already exists.
+
+Behavior on invocation with `null` values must be defined for each
+function. There are two options:
+
+. `RETURNS NULL ON NULL INPUT` declares that the function will always
+return `null` if any of the input arguments is `null`.
+. `CALLED ON NULL INPUT` declares that the function will always be
+executed.
+
+If the optional `IF NOT EXISTS` keywords are used, the function will
+only be created if another function with the same signature does not
+exist.
+
+`OR REPLACE` and `IF NOT EXIST` cannot be used together.
+
+Functions belong to a keyspace. If no keyspace is specified in
+`<function-name>`, the current keyspace is used (i.e. the keyspace
+specified using the link:#useStmt[`USE`] statement). It is not possible
+to create a user-defined function in one of the system keyspaces.
+
+See the section on link:#udfs[user-defined functions] for more
+information.
+
+[[dropFunctionStmt]]
+==== DROP FUNCTION
+
+_Syntax:_
+
+bc(syntax).. +
+::= DROP FUNCTION ( IF EXISTS )? +
+( `.' )? +
+( `(' ( `,' )* `)' )?
+
+_Sample:_
+
+bc(sample). +
+DROP FUNCTION myfunction; +
+DROP FUNCTION mykeyspace.afunction; +
+DROP FUNCTION afunction ( int ); +
+DROP FUNCTION afunction ( text );
+
+`DROP FUNCTION` statement removes a function created using
+`CREATE FUNCTION`. +
+You must specify the argument types (link:#functionSignature[signature]
+) of the function to drop if there are multiple functions with the same
+name but a different signature (overloaded functions).
+
+`DROP FUNCTION` with the optional `IF EXISTS` keywords drops a function
+if it exists.
+
+[[createAggregateStmt]]
+==== CREATE AGGREGATE
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE ( OR REPLACE )? +
+AGGREGATE ( IF NOT EXISTS )? +
+( `.' )? +
+`(' ( `,' )* `)' +
+SFUNC +
+STYPE +
+( FINALFUNC )? +
+( INITCOND )? +
+p. +
+_Sample:_
+
+bc(sample). +
+CREATE AGGREGATE myaggregate ( val text ) +
+SFUNC myaggregate_state +
+STYPE text +
+FINALFUNC myaggregate_final +
+INITCOND `foo';
+
+See the section on link:#udas[user-defined aggregates] for a complete
+example.
+
+`CREATE AGGREGATE` creates or replaces a user-defined aggregate.
+
+`CREATE AGGREGATE` with the optional `OR REPLACE` keywords either
+creates an aggregate or replaces an existing one with the same
+signature. A `CREATE AGGREGATE` without `OR REPLACE` fails if an
+aggregate with the same signature already exists.
+
+`CREATE AGGREGATE` with the optional `IF NOT EXISTS` keywords either
+creates an aggregate if it does not already exist.
+
+`OR REPLACE` and `IF NOT EXIST` cannot be used together.
+
+Aggregates belong to a keyspace. If no keyspace is specified in
+`<aggregate-name>`, the current keyspace is used (i.e. the keyspace
+specified using the link:#useStmt[`USE`] statement). It is not possible
+to create a user-defined aggregate in one of the system keyspaces.
+
+Signatures for user-defined aggregates follow the
+link:#functionSignature[same rules] as for user-defined functions.
+
+`STYPE` defines the type of the state value and must be specified.
+
+The optional `INITCOND` defines the initial state value for the
+aggregate. It defaults to `null`. A non-`null` `INITCOND` must be
+specified for state functions that are declared with
+`RETURNS NULL ON NULL INPUT`.
+
+`SFUNC` references an existing function to be used as the state
+modifying function. The type of first argument of the state function
+must match `STYPE`. The remaining argument types of the state function
+must match the argument types of the aggregate function. State is not
+updated for state functions declared with `RETURNS NULL ON NULL INPUT`
+and called with `null`.
+
+The optional `FINALFUNC` is called just before the aggregate result is
+returned. It must take only one argument with type `STYPE`. The return
+type of the `FINALFUNC` may be a different type. A final function
+declared with `RETURNS NULL ON NULL INPUT` means that the aggregate’s
+return value will be `null`, if the last state is `null`.
+
+If no `FINALFUNC` is defined, the overall return type of the aggregate
+function is `STYPE`. If a `FINALFUNC` is defined, it is the return type
+of that function.
+
+See the section on link:#udas[user-defined aggregates] for more
+information.
+
+[[dropAggregateStmt]]
+==== DROP AGGREGATE
+
+_Syntax:_
+
+bc(syntax).. +
+::= DROP AGGREGATE ( IF EXISTS )? +
+( `.' )? +
+( `(' ( `,' )* `)' )? +
+p.
+
+_Sample:_
+
+bc(sample). +
+DROP AGGREGATE myAggregate; +
+DROP AGGREGATE myKeyspace.anAggregate; +
+DROP AGGREGATE someAggregate ( int ); +
+DROP AGGREGATE someAggregate ( text );
+
+The `DROP AGGREGATE` statement removes an aggregate created using
+`CREATE AGGREGATE`. You must specify the argument types of the aggregate
+to drop if there are multiple aggregates with the same name but a
+different signature (overloaded aggregates).
+
+`DROP AGGREGATE` with the optional `IF EXISTS` keywords drops an
+aggregate if it exists, and does nothing if a function with the
+signature does not exist.
+
+Signatures for user-defined aggregates follow the
+link:#functionSignature[same rules] as for user-defined functions.
+
+[[dataManipulation]]
+=== Data Manipulation
+
+[[insertStmt]]
+==== INSERT
+
+_Syntax:_
+
+bc(syntax).. +
+::= INSERT INTO +
+( ( VALUES ) +
+| ( JSON )) +
+( IF NOT EXISTS )? +
+( USING ( AND )* )?
+
+::= `(' ( `,' )* `)'
+
+::= `(' ( `,' )* `)'
+
+::= TIMESTAMP +
+| TTL +
+p. +
+_Sample:_
+
+bc(sample).. +
+INSERT INTO NerdMovies (movie, director, main_actor, year) +
+VALUES (`Serenity', `Joss Whedon', `Nathan Fillion', 2005) +
+USING TTL 86400;
+
+INSERT INTO NerdMovies JSON `\{``movie'': ``Serenity'', ``director'':
+``Joss Whedon'', ``year'': 2005}' +
+p. +
+The `INSERT` statement writes one or more columns for a given row in a
+table. Note that since a row is identified by its `PRIMARY KEY`, at
+least the columns composing it must be specified. The list of columns to
+insert to must be supplied when using the `VALUES` syntax. When using
+the `JSON` syntax, they are optional. See the section on
+link:#insertJson[`INSERT JSON`] for more details.
+
+Note that unlike in SQL, `INSERT` does not check the prior existence of
+the row by default: the row is created if none existed before, and
+updated otherwise. Furthermore, there is no mean to know which of
+creation or update happened.
+
+It is however possible to use the `IF NOT EXISTS` condition to only
+insert if the row does not exist prior to the insertion. But please note
+that using `IF NOT EXISTS` will incur a non negligible performance cost
+(internally, Paxos will be used) so this should be used sparingly.
+
+All updates for an `INSERT` are applied atomically and in isolation.
+
+Please refer to the link:#updateOptions[`UPDATE`] section for
+information on the `<option>` available and to the
+link:#collections[collections] section for use of
+`<collection-literal>`. Also note that `INSERT` does not support
+counters, while `UPDATE` does.
+
+[[updateStmt]]
+==== UPDATE
+
+_Syntax:_
+
+bc(syntax).. +
+::= UPDATE +
+( USING ( AND )* )? +
+SET ( `,' )* +
+WHERE +
+( IF ( AND condition )* )?
+
+::= `=' +
+| `=' (`+' | `-') ( | | ) +
+| `=' `+' +
+| `[' `]' `=' +
+| `.' `='
+
+::= +
+| IN +
+| `[' `]' +
+| `[' `]' IN +
+| `.' +
+| `.' IN
+
+::= `<' | `<=' | `=' | `!=' | `>=' | `>' +
+::= ( | `(' ( ( `,' )* )? `)')
+
+::= ( AND )*
+
+::= `=' +
+| `(' (`,' )* `)' `=' +
+| IN `(' ( ( `,' )* )? `)' +
+| IN +
+| `(' (`,' )* `)' IN `(' ( ( `,' )* )? `)' +
+| `(' (`,' )* `)' IN
+
+::= TIMESTAMP +
+| TTL +
+p. +
+_Sample:_
+
+bc(sample).. +
+UPDATE NerdMovies USING TTL 400 +
+SET director = `Joss Whedon', +
+main_actor = `Nathan Fillion', +
+year = 2005 +
+WHERE movie = `Serenity';
+
+UPDATE UserActions SET total = total + 2 WHERE user =
+B70DE1D0-9908-4AE3-BE34-5573E5B09F14 AND action = `click'; +
+p. +
+The `UPDATE` statement writes one or more columns for a given row in a
+table. The `<where-clause>` is used to select the row to update and must
+include all columns composing the `PRIMARY KEY`. Other columns values
+are specified through `<assignment>` after the `SET` keyword.
+
+Note that unlike in SQL, `UPDATE` does not check the prior existence of
+the row by default (except through the use of `<condition>`, see below):
+the row is created if none existed before, and updated otherwise.
+Furthermore, there are no means to know whether a creation or update
+occurred.
+
+It is however possible to use the conditions on some columns through
+`IF`, in which case the row will not be updated unless the conditions
+are met. But, please note that using `IF` conditions will incur a
+non-negligible performance cost (internally, Paxos will be used) so this
+should be used sparingly.
+
+In an `UPDATE` statement, all updates within the same partition key are
+applied atomically and in isolation.
+
+The `c = c + 3` form of `<assignment>` is used to increment/decrement
+counters. The identifier after the `=' sign *must* be the same than the
+one before the `=' sign (Only increment/decrement is supported on
+counters, not the assignment of a specific value).
+
+The `id = id + <collection-literal>` and `id[value1] = value2` forms of
+`<assignment>` are for collections. Please refer to the
+link:#collections[relevant section] for more details.
+
+The `id.field = <term>` form of `<assignemt>` is for setting the value
+of a single field on a non-frozen user-defined types.
+
+[[updateOptions]]
+===== `<options>`
+
+The `UPDATE` and `INSERT` statements support the following options:
+
+* `TIMESTAMP`: sets the timestamp for the operation. If not specified,
+the coordinator will use the current time (in microseconds) at the start
+of statement execution as the timestamp. This is usually a suitable
+default.
+* `TTL`: specifies an optional Time To Live (in seconds) for the
+inserted values. If set, the inserted values are automatically removed
+from the database after the specified time. Note that the TTL concerns
+the inserted values, not the columns themselves. This means that any
+subsequent update of the column will also reset the TTL (to whatever TTL
+is specified in that update). By default, values never expire. A TTL of
+0 is equivalent to no TTL. If the table has a default_time_to_live, a
+TTL of 0 will remove the TTL for the inserted or updated values.
+
+[[deleteStmt]]
+==== DELETE
+
+_Syntax:_
+
+bc(syntax).. +
+::= DELETE ( ( `,' )* )? +
+FROM +
+( USING TIMESTAMP )? +
+WHERE +
+( IF ( EXISTS | ( ( AND )*) ) )?
+
+::= +
+| `[' `]' +
+| `.'
+
+::= ( AND )*
+
+::= +
+| `(' (`,' )* `)' +
+| IN `(' ( ( `,' )* )? `)' +
+| IN +
+| `(' (`,' )* `)' IN `(' ( ( `,' )* )? `)' +
+| `(' (`,' )* `)' IN
+
+::= `=' | `<' | `>' | `<=' | `>=' +
+::= ( | `(' ( ( `,' )* )? `)')
+
+::= ( | `!=') +
+| IN +
+| `[' `]' ( | `!=') +
+| `[' `]' IN +
+| `.' ( | `!=') +
+| `.' IN
+
+_Sample:_
+
+bc(sample).. +
+DELETE FROM NerdMovies USING TIMESTAMP 1240003134 WHERE movie =
+`Serenity';
+
+DELETE phone FROM Users WHERE userid IN
+(C73DE1D3-AF08-40F3-B124-3FF3E5109F22,
+B70DE1D0-9908-4AE3-BE34-5573E5B09F14); +
+p. +
+The `DELETE` statement deletes columns and rows. If column names are
+provided directly after the `DELETE` keyword, only those columns are
+deleted from the row indicated by the `<where-clause>`. The `id[value]`
+syntax in `<selection>` is for non-frozen collections (please refer to
+the link:#collections[collection section] for more details). The
+`id.field` syntax is for the deletion of non-frozen user-defined types.
+Otherwise, whole rows are removed. The `<where-clause>` specifies which
+rows are to be deleted. Multiple rows may be deleted with one statement
+by using an `IN` clause. A range of rows may be deleted using an
+inequality operator (such as `>=`).
+
+`DELETE` supports the `TIMESTAMP` option with the same semantics as the
+link:#updateStmt[`UPDATE`] statement.
+
+In a `DELETE` statement, all deletions within the same partition key are
+applied atomically and in isolation.
+
+A `DELETE` operation can be conditional through the use of an `IF`
+clause, similar to `UPDATE` and `INSERT` statements. However, as with
+`INSERT` and `UPDATE` statements, this will incur a non-negligible
+performance cost (internally, Paxos will be used) and so should be used
+sparingly.
+
+[[batchStmt]]
+==== BATCH
+
+_Syntax:_
+
+bc(syntax).. +
+::= BEGIN ( UNLOGGED | COUNTER ) BATCH +
+( USING ( AND )* )? +
+( `;' )* +
+APPLY BATCH
+
+::= +
+| +
+|
+
+::= TIMESTAMP +
+p. +
+_Sample:_
+
+bc(sample). +
+BEGIN BATCH +
+INSERT INTO users (userid, password, name) VALUES (`user2', `ch@ngem3b',
+`second user'); +
+UPDATE users SET password = `ps22dhds' WHERE userid = `user3'; +
+INSERT INTO users (userid, password) VALUES (`user4', `ch@ngem3c'); +
+DELETE name FROM users WHERE userid = `user1'; +
+APPLY BATCH;
+
+The `BATCH` statement group multiple modification statements
+(insertions/updates and deletions) into a single statement. It serves
+several purposes:
+
+. It saves network round-trips between the client and the server (and
+sometimes between the server coordinator and the replicas) when batching
+multiple updates.
+. All updates in a `BATCH` belonging to a given partition key are
+performed in isolation.
+. By default, all operations in the batch are performed as `LOGGED`, to
+ensure all mutations eventually complete (or none will). See the notes
+on link:#unloggedBatch[`UNLOGGED`] for more details.
+
+Note that:
+
+* `BATCH` statements may only contain `UPDATE`, `INSERT` and `DELETE`
+statements.
+* Batches are _not_ a full analogue for SQL transactions.
+* If a timestamp is not specified for each operation, then all
+operations will be applied with the same timestamp. Due to Cassandra’s
+conflict resolution procedure in the case of
+http://wiki.apache.org/cassandra/FAQ#clocktie[timestamp ties],
+operations may be applied in an order that is different from the order
+they are listed in the `BATCH` statement. To force a particular
+operation ordering, you must specify per-operation timestamps.
+
+[[unloggedBatch]]
+===== `UNLOGGED`
+
+By default, Cassandra uses a batch log to ensure all operations in a
+batch eventually complete or none will (note however that operations are
+only isolated within a single partition).
+
+There is a performance penalty for batch atomicity when a batch spans
+multiple partitions. If you do not want to incur this penalty, you can
+tell Cassandra to skip the batchlog with the `UNLOGGED` option. If the
+`UNLOGGED` option is used, a failed batch might leave the patch only
+partly applied.
+
+[[counterBatch]]
+===== `COUNTER`
+
+Use the `COUNTER` option for batched counter updates. Unlike other
+updates in Cassandra, counter updates are not idempotent.
+
+[[batchOptions]]
+===== `<option>`
+
+`BATCH` supports both the `TIMESTAMP` option, with similar semantic to
+the one described in the link:#updateOptions[`UPDATE`] statement (the
+timestamp applies to all the statement inside the batch). However, if
+used, `TIMESTAMP` *must not* be used in the statements within the batch.
+
+=== Queries
+
+[[selectStmt]]
+==== SELECT
+
+_Syntax:_
+
+bc(syntax).. +
+::= SELECT ( JSON )? +
+FROM +
+( WHERE )? +
+( GROUP BY )? +
+( ORDER BY )? +
+( PER PARTITION LIMIT )? +
+( LIMIT )? +
+( ALLOW FILTERING )?
+
+::= DISTINCT?
+
+::= (AS )? ( `,' (AS )? )* +
+| `*'
+
+::= +
+| +
+| WRITETIME `(' `)' +
+| COUNT `(' `*' `)' +
+| TTL `(' `)' +
+| CAST `(' AS `)' +
+| `(' ( (`,' )*)? `)' +
+| `.' +
+| `[' `]' +
+| `[' ? .. ? `]'
+
+::= ( AND )*
+
+::= +
+| `(' (`,' )* `)' +
+| IN `(' ( ( `,' )* )? `)' +
+| `(' (`,' )* `)' IN `(' ( ( `,' )* )? `)' +
+| TOKEN `(' ( `,' )* `)'
+
+::= `=' | `<' | `>' | `<=' | `>=' | CONTAINS | CONTAINS KEY +
+::= (`,' )* +
+::= ( `,' )* +
+::= ( ASC | DESC )? +
+::= `(' (`,' )* `)' +
+p. +
+_Sample:_
+
+bc(sample).. +
+SELECT name, occupation FROM users WHERE userid IN (199, 200, 207);
+
+SELECT JSON name, occupation FROM users WHERE userid = 199;
+
+SELECT name AS user_name, occupation AS user_occupation FROM users;
+
+SELECT time, value +
+FROM events +
+WHERE event_type = `myEvent' +
+AND time > `2011-02-03' +
+AND time <= `2012-01-01'
+
+SELECT COUNT (*) FROM users;
+
+SELECT COUNT (*) AS user_count FROM users;
+
+The `SELECT` statements reads one or more columns for one or more rows
+in a table. It returns a result-set of rows, where each row contains the
+collection of columns corresponding to the query. If the `JSON` keyword
+is used, the results for each row will contain only a single column
+named ``json''. See the section on link:#selectJson[`SELECT JSON`] for
+more details.
+
+[[selectSelection]]
+===== `<select-clause>`
+
+The `<select-clause>` determines which columns needs to be queried and
+returned in the result-set. It consists of either the comma-separated
+list of or the wildcard character (`*`) to select all the columns
+defined for the table. Please note that for wildcard `SELECT` queries
+the order of columns returned is not specified and is not guaranteed to
+be stable between Cassandra versions.
+
+A `<selector>` is either a column name to retrieve or a `<function>` of
+one or more `<term>`s. The function allowed are the same as for `<term>`
+and are described in the link:#functions[function section]. In addition
+to these generic functions, the `WRITETIME` (resp. `TTL`) function
+allows to select the timestamp of when the column was inserted (resp.
+the time to live (in seconds) for the column (or null if the column has
+no expiration set)) and the link:#castFun[`CAST`] function can be used
- to convert one data type to another.
++to convert one data type to another. The `WRITETIME` and `TTL` functions
++can't be used on multi-cell columns such as non-frozen collections or
++non-frozen user-defined types.
+
+Additionally, individual values of maps and sets can be selected using
+`[ <term> ]`. For maps, this will return the value corresponding to the
+key, if such entry exists. For sets, this will return the key that is
+selected if it exists and is thus mainly a way to check element
+existence. It is also possible to select a slice of a set or map with
+`[ <term> ... <term> `], where both bound can be omitted.
+
+Any `<selector>` can be aliased using `AS` keyword (see examples).
+Please note that `<where-clause>` and `<order-by>` clause should refer
+to the columns by their original names and not by their aliases.
+
+The `COUNT` keyword can be used with parenthesis enclosing `*`. If so,
+the query will return a single result: the number of rows matching the
+query. Note that `COUNT(1)` is supported as an alias.
+
+[[selectWhere]]
+===== `<where-clause>`
+
+The `<where-clause>` specifies which rows must be queried. It is
+composed of relations on the columns that are part of the `PRIMARY KEY`
+and/or have a link:#createIndexStmt[secondary index] defined on them.
+
+Not all relations are allowed in a query. For instance, non-equal
+relations (where `IN` is considered as an equal relation) on a partition
+key are not supported (but see the use of the `TOKEN` method below to do
+non-equal queries on the partition key). Moreover, for a given partition
+key, the clustering columns induce an ordering of rows and relations on
+them is restricted to the relations that allow to select a *contiguous*
+(for the ordering) set of rows. For instance, given
+
+bc(sample). +
+CREATE TABLE posts ( +
+userid text, +
+blog_title text, +
+posted_at timestamp, +
+entry_title text, +
+content text, +
+category int, +
+PRIMARY KEY (userid, blog_title, posted_at) +
+)
+
+The following query is allowed:
+
+bc(sample). +
+SELECT entry_title, content FROM posts WHERE userid=`john doe' AND
+blog_title=`John'`s Blog' AND posted_at >= `2012-01-01' AND posted_at <
+`2012-01-31'
+
+But the following one is not, as it does not select a contiguous set of
+rows (and we suppose no secondary indexes are set):
+
+bc(sample). +
+// Needs a blog_title to be set to select ranges of posted_at +
+SELECT entry_title, content FROM posts WHERE userid=`john doe' AND
+posted_at >= `2012-01-01' AND posted_at < `2012-01-31'
+
+When specifying relations, the `TOKEN` function can be used on the
+`PARTITION KEY` column to query. In that case, rows will be selected
+based on the token of their `PARTITION_KEY` rather than on the value.
+Note that the token of a key depends on the partitioner in use, and that
+in particular the RandomPartitioner won’t yield a meaningful order. Also
+note that ordering partitioners always order token values by bytes (so
+even if the partition key is of type int, `token(-1) > token(0)` in
+particular). Example:
+
+bc(sample). +
+SELECT * FROM posts WHERE token(userid) > token(`tom') AND token(userid)
+< token(`bob')
+
+Moreover, the `IN` relation is only allowed on the last column of the
+partition key and on the last column of the full primary key.
+
+It is also possible to ``group'' `CLUSTERING COLUMNS` together in a
+relation using the tuple notation. For instance:
+
+bc(sample). +
+SELECT * FROM posts WHERE userid=`john doe' AND (blog_title, posted_at)
+> (`John'`s Blog', `2012-01-01')
+
+will request all rows that sorts after the one having ``John’s Blog'' as
+`blog_tile` and `2012-01-01' for `posted_at` in the clustering order. In
+particular, rows having a `post_at <= '2012-01-01'` will be returned as
+long as their `blog_title > 'John''s Blog'`, which wouldn’t be the case
+for:
+
+bc(sample). +
+SELECT * FROM posts WHERE userid=`john doe' AND blog_title > `John'`s
+Blog' AND posted_at > `2012-01-01'
+
+The tuple notation may also be used for `IN` clauses on
+`CLUSTERING COLUMNS`:
+
+bc(sample). +
+SELECT * FROM posts WHERE userid=`john doe' AND (blog_title, posted_at)
+IN ((`John'`s Blog', `2012-01-01), (’Extreme Chess', `2014-06-01'))
+
+The `CONTAINS` operator may only be used on collection columns (lists,
+sets, and maps). In the case of maps, `CONTAINS` applies to the map
+values. The `CONTAINS KEY` operator may only be used on map columns and
+applies to the map keys.
+
+[[selectOrderBy]]
+===== `<order-by>`
+
+The `ORDER BY` option allows to select the order of the returned
+results. It takes as argument a list of column names along with the
+order for the column (`ASC` for ascendant and `DESC` for descendant,
+omitting the order being equivalent to `ASC`). Currently the possible
+orderings are limited (which depends on the table
+link:#createTableOptions[`CLUSTERING ORDER`] ):
+
+* if the table has been defined without any specific `CLUSTERING ORDER`,
+then then allowed orderings are the order induced by the clustering
+columns and the reverse of that one.
+* otherwise, the orderings allowed are the order of the
+`CLUSTERING ORDER` option and the reversed one.
+
+[[selectGroupBy]]
+===== `<group-by>`
+
+The `GROUP BY` option allows to condense into a single row all selected
+rows that share the same values for a set of columns.
+
+Using the `GROUP BY` option, it is only possible to group rows at the
+partition key level or at a clustering column level. By consequence, the
+`GROUP BY` option only accept as arguments primary key column names in
+the primary key order. If a primary key column is restricted by an
+equality restriction it is not required to be present in the `GROUP BY`
+clause.
+
+Aggregate functions will produce a separate value for each group. If no
+`GROUP BY` clause is specified, aggregates functions will produce a
+single value for all the rows.
+
+If a column is selected without an aggregate function, in a statement
+with a `GROUP BY`, the first value encounter in each group will be
+returned.
+
+[[selectLimit]]
+===== `LIMIT` and `PER PARTITION LIMIT`
+
+The `LIMIT` option to a `SELECT` statement limits the number of rows
+returned by a query, while the `PER PARTITION LIMIT` option limits the
+number of rows returned for a given partition by the query. Note that
+both type of limit can used in the same statement.
+
+[[selectAllowFiltering]]
+===== `ALLOW FILTERING`
+
+By default, CQL only allows select queries that don’t involve
+``filtering'' server side, i.e. queries where we know that all (live)
+record read will be returned (maybe partly) in the result set. The
+reasoning is that those ``non filtering'' queries have predictable
+performance in the sense that they will execute in a time that is
+proportional to the amount of data *returned* by the query (which can be
+controlled through `LIMIT`).
+
+The `ALLOW FILTERING` option allows to explicitly allow (some) queries
+that require filtering. Please note that a query using `ALLOW FILTERING`
+may thus have unpredictable performance (for the definition above), i.e.
+even a query that selects a handful of records *may* exhibit performance
+that depends on the total amount of data stored in the cluster.
+
+For instance, considering the following table holding user profiles with
+their year of birth (with a secondary index on it) and country of
+residence:
+
+bc(sample).. +
+CREATE TABLE users ( +
+username text PRIMARY KEY, +
+firstname text, +
+lastname text, +
+birth_year int, +
+country text +
+)
+
+CREATE INDEX ON users(birth_year); +
+p.
+
+Then the following queries are valid:
+
+bc(sample). +
+SELECT * FROM users; +
+SELECT firstname, lastname FROM users WHERE birth_year = 1981;
+
+because in both case, Cassandra guarantees that these queries
+performance will be proportional to the amount of data returned. In
+particular, if no users are born in 1981, then the second query
+performance will not depend of the number of user profile stored in the
+database (not directly at least: due to secondary index implementation
+consideration, this query may still depend on the number of node in the
+cluster, which indirectly depends on the amount of data stored.
+Nevertheless, the number of nodes will always be multiple number of
+magnitude lower than the number of user profile stored). Of course, both
+query may return very large result set in practice, but the amount of
+data returned can always be controlled by adding a `LIMIT`.
+
+However, the following query will be rejected:
+
+bc(sample). +
+SELECT firstname, lastname FROM users WHERE birth_year = 1981 AND
+country = `FR';
+
+because Cassandra cannot guarantee that it won’t have to scan large
+amount of data even if the result to those query is small. Typically, it
+will scan all the index entries for users born in 1981 even if only a
+handful are actually from France. However, if you ``know what you are
+doing'', you can force the execution of this query by using
+`ALLOW FILTERING` and so the following query is valid:
+
+bc(sample). +
+SELECT firstname, lastname FROM users WHERE birth_year = 1981 AND
+country = `FR' ALLOW FILTERING;
+
+[[databaseRoles]]
+=== Database Roles
+
+[[createRoleStmt]]
+==== CREATE ROLE
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE ROLE ( IF NOT EXISTS )? ( WITH ( AND )* )?
+
+::= PASSWORD = +
+| LOGIN = +
+| SUPERUSER = +
+| OPTIONS = +
+p.
+
+_Sample:_
+
+bc(sample). +
+CREATE ROLE new_role; +
+CREATE ROLE alice WITH PASSWORD = `password_a' AND LOGIN = true; +
+CREATE ROLE bob WITH PASSWORD = `password_b' AND LOGIN = true AND
+SUPERUSER = true; +
+CREATE ROLE carlos WITH OPTIONS = \{ `custom_option1' : `option1_value',
+`custom_option2' : 99 };
+
+By default roles do not possess `LOGIN` privileges or `SUPERUSER`
+status.
+
+link:#permissions[Permissions] on database resources are granted to
+roles; types of resources include keyspaces, tables, functions and roles
+themselves. Roles may be granted to other roles to create hierarchical
+permissions structures; in these hierarchies, permissions and
+`SUPERUSER` status are inherited, but the `LOGIN` privilege is not.
+
+If a role has the `LOGIN` privilege, clients may identify as that role
+when connecting. For the duration of that connection, the client will
+acquire any roles and privileges granted to that role.
+
+Only a client with with the `CREATE` permission on the database roles
+resource may issue `CREATE ROLE` requests (see the
+link:#permissions[relevant section] below), unless the client is a
+`SUPERUSER`. Role management in Cassandra is pluggable and custom
+implementations may support only a subset of the listed options.
+
+Role names should be quoted if they contain non-alphanumeric characters.
+
+[[createRolePwd]]
+===== Setting credentials for internal authentication
+
+Use the `WITH PASSWORD` clause to set a password for internal
+authentication, enclosing the password in single quotation marks. +
+If internal authentication has not been set up or the role does not have
+`LOGIN` privileges, the `WITH PASSWORD` clause is not necessary.
+
+[[createRoleConditional]]
+===== Creating a role conditionally
+
+Attempting to create an existing role results in an invalid query
+condition unless the `IF NOT EXISTS` option is used. If the option is
+used and the role exists, the statement is a no-op.
+
+bc(sample). +
+CREATE ROLE other_role; +
+CREATE ROLE IF NOT EXISTS other_role;
+
+[[alterRoleStmt]]
+==== ALTER ROLE
+
+_Syntax:_
+
+bc(syntax).. +
+::= ALTER ROLE ( WITH ( AND )* )?
+
+::= PASSWORD = +
+| LOGIN = +
+| SUPERUSER = +
+| OPTIONS = +
+p.
+
+_Sample:_
+
+bc(sample). +
+ALTER ROLE bob WITH PASSWORD = `PASSWORD_B' AND SUPERUSER = false;
+
+Conditions on executing `ALTER ROLE` statements:
+
+* A client must have `SUPERUSER` status to alter the `SUPERUSER` status
+of another role
+* A client cannot alter the `SUPERUSER` status of any role it currently
+holds
+* A client can only modify certain properties of the role with which it
+identified at login (e.g. `PASSWORD`)
+* To modify properties of a role, the client must be granted `ALTER`
+link:#permissions[permission] on that role
+
+[[dropRoleStmt]]
+==== DROP ROLE
+
+_Syntax:_
+
+bc(syntax).. +
+::= DROP ROLE ( IF EXISTS )? +
+p.
+
+_Sample:_
+
+bc(sample). +
+DROP ROLE alice; +
+DROP ROLE IF EXISTS bob;
+
+`DROP ROLE` requires the client to have `DROP`
+link:#permissions[permission] on the role in question. In addition,
+client may not `DROP` the role with which it identified at login.
+Finaly, only a client with `SUPERUSER` status may `DROP` another
+`SUPERUSER` role. +
+Attempting to drop a role which does not exist results in an invalid
+query condition unless the `IF EXISTS` option is used. If the option is
+used and the role does not exist the statement is a no-op.
+
+[[grantRoleStmt]]
+==== GRANT ROLE
+
+_Syntax:_
+
+bc(syntax). +
+::= GRANT TO
+
+_Sample:_
+
+bc(sample). +
+GRANT report_writer TO alice;
+
+This statement grants the `report_writer` role to `alice`. Any
+permissions granted to `report_writer` are also acquired by `alice`. +
+Roles are modelled as a directed acyclic graph, so circular grants are
+not permitted. The following examples result in error conditions:
+
+bc(sample). +
+GRANT role_a TO role_b; +
+GRANT role_b TO role_a;
+
+bc(sample). +
+GRANT role_a TO role_b; +
+GRANT role_b TO role_c; +
+GRANT role_c TO role_a;
+
+[[revokeRoleStmt]]
+==== REVOKE ROLE
+
+_Syntax:_
+
+bc(syntax). +
+::= REVOKE FROM
+
+_Sample:_
+
+bc(sample). +
+REVOKE report_writer FROM alice;
+
+This statement revokes the `report_writer` role from `alice`. Any
+permissions that `alice` has acquired via the `report_writer` role are
+also revoked.
+
+[[listRolesStmt]]
+===== LIST ROLES
+
+_Syntax:_
+
+bc(syntax). +
+::= LIST ROLES ( OF )? ( NORECURSIVE )?
+
+_Sample:_
+
+bc(sample). +
+LIST ROLES;
+
+Return all known roles in the system, this requires `DESCRIBE`
+permission on the database roles resource.
+
+bc(sample). +
+LIST ROLES OF `alice`;
+
+Enumerate all roles granted to `alice`, including those transitively
+aquired.
+
+bc(sample). +
+LIST ROLES OF `bob` NORECURSIVE
+
+List all roles directly granted to `bob`.
+
+[[createUserStmt]]
+==== CREATE USER
+
+Prior to the introduction of roles in Cassandra 2.2, authentication and
+authorization were based around the concept of a `USER`. For backward
+compatibility, the legacy syntax has been preserved with `USER` centric
+statments becoming synonyms for the `ROLE` based equivalents.
+
+_Syntax:_
+
+bc(syntax).. +
+::= CREATE USER ( IF NOT EXISTS )? ( WITH PASSWORD )? ()?
+
+::= SUPERUSER +
+| NOSUPERUSER +
+p.
+
+_Sample:_
+
+bc(sample). +
+CREATE USER alice WITH PASSWORD `password_a' SUPERUSER; +
+CREATE USER bob WITH PASSWORD `password_b' NOSUPERUSER;
+
+`CREATE USER` is equivalent to `CREATE ROLE` where the `LOGIN` option is
+`true`. So, the following pairs of statements are equivalent:
+
+bc(sample).. +
+CREATE USER alice WITH PASSWORD `password_a' SUPERUSER; +
+CREATE ROLE alice WITH PASSWORD = `password_a' AND LOGIN = true AND
+SUPERUSER = true;
+
+CREATE USER IF NOT EXISTS alice WITH PASSWORD `password_a' SUPERUSER; +
+CREATE ROLE IF NOT EXISTS alice WITH PASSWORD = `password_a' AND LOGIN =
+true AND SUPERUSER = true;
+
+CREATE USER alice WITH PASSWORD `password_a' NOSUPERUSER; +
+CREATE ROLE alice WITH PASSWORD = `password_a' AND LOGIN = true AND
+SUPERUSER = false;
+
+CREATE USER alice WITH PASSWORD `password_a' NOSUPERUSER; +
+CREATE ROLE alice WITH PASSWORD = `password_a' AND LOGIN = true;
+
+CREATE USER alice WITH PASSWORD `password_a'; +
+CREATE ROLE alice WITH PASSWORD = `password_a' AND LOGIN = true; +
+p.
+
+[[alterUserStmt]]
+==== ALTER USER
+
+_Syntax:_
+
+bc(syntax).. +
+::= ALTER USER ( WITH PASSWORD )? ( )?
+
+::= SUPERUSER +
+| NOSUPERUSER +
+p.
+
+bc(sample). +
+ALTER USER alice WITH PASSWORD `PASSWORD_A'; +
+ALTER USER bob SUPERUSER;
+
+[[dropUserStmt]]
+==== DROP USER
+
+_Syntax:_
+
+bc(syntax).. +
+::= DROP USER ( IF EXISTS )? +
+p.
+
+_Sample:_
+
+bc(sample). +
+DROP USER alice; +
+DROP USER IF EXISTS bob;
+
+[[listUsersStmt]]
+==== LIST USERS
+
+_Syntax:_
+
+bc(syntax). +
+::= LIST USERS;
+
+_Sample:_
+
+bc(sample). +
+LIST USERS;
+
+This statement is equivalent to
+
+bc(sample). +
+LIST ROLES;
+
+but only roles with the `LOGIN` privilege are included in the output.
+
+[[dataControl]]
+=== Data Control
+
+==== Permissions
+
+Permissions on resources are granted to roles; there are several
+different types of resources in Cassandra and each type is modelled
+hierarchically:
+
+* The hierarchy of Data resources, Keyspaces and Tables has the
+structure `ALL KEYSPACES` -> `KEYSPACE` -> `TABLE`
+* Function resources have the structure `ALL FUNCTIONS` -> `KEYSPACE` ->
+`FUNCTION`
+* Resources representing roles have the structure `ALL ROLES` -> `ROLE`
+* Resources representing JMX ObjectNames, which map to sets of
+MBeans/MXBeans, have the structure `ALL MBEANS` -> `MBEAN`
+
+Permissions can be granted at any level of these hierarchies and they
+flow downwards. So granting a permission on a resource higher up the
+chain automatically grants that same permission on all resources lower
+down. For example, granting `SELECT` on a `KEYSPACE` automatically
+grants it on all `TABLES` in that `KEYSPACE`. Likewise, granting a
+permission on `ALL FUNCTIONS` grants it on every defined function,
+regardless of which keyspace it is scoped in. It is also possible to
+grant permissions on all functions scoped to a particular keyspace.
+
+Modifications to permissions are visible to existing client sessions;
+that is, connections need not be re-established following permissions
+changes.
+
+The full set of available permissions is:
+
+* `CREATE`
+* `ALTER`
+* `DROP`
+* `SELECT`
+* `MODIFY`
+* `AUTHORIZE`
+* `DESCRIBE`
+* `EXECUTE`
+
+Not all permissions are applicable to every type of resource. For
+instance, `EXECUTE` is only relevant in the context of functions or
+mbeans; granting `EXECUTE` on a resource representing a table is
+nonsensical. Attempting to `GRANT` a permission on resource to which it
+cannot be applied results in an error response. The following
+illustrates which permissions can be granted on which types of resource,
+and which statements are enabled by that permission.
+
+[cols=",,,,,",options="header",]
+|===
+|permission |resource |operations | | |
+|`CREATE` |`ALL KEYSPACES` |`CREATE KEYSPACE` <br> `CREATE TABLE` in any
+keyspace | | |
+
+|`CREATE` |`KEYSPACE` |`CREATE TABLE` in specified keyspace | | |
+
+|`CREATE` |`ALL FUNCTIONS` |`CREATE FUNCTION` in any keyspace <br>
+`CREATE AGGREGATE` in any keyspace | | |
+
+|`CREATE` |`ALL FUNCTIONS IN KEYSPACE` |`CREATE FUNCTION` in keyspace
+<br> `CREATE AGGREGATE` in keyspace | | |
+
+|`CREATE` |`ALL ROLES` |`CREATE ROLE` | | |
+
+|`ALTER` |`ALL KEYSPACES` |`ALTER KEYSPACE` <br> `ALTER TABLE` in any
+keyspace | | |
+
+|`ALTER` |`KEYSPACE` |`ALTER KEYSPACE` <br> `ALTER TABLE` in keyspace |
+| |
+
+|`ALTER` |`TABLE` |`ALTER TABLE` | | |
+
+|`ALTER` |`ALL FUNCTIONS` |`CREATE FUNCTION` replacing any existing <br>
+`CREATE AGGREGATE` replacing any existing | | |
+
+|`ALTER` |`ALL FUNCTIONS IN KEYSPACE` |`CREATE FUNCTION` replacing
+existing in keyspace <br> `CREATE AGGREGATE` replacing any existing in
+keyspace | | |
+
+|`ALTER` |`FUNCTION` |`CREATE FUNCTION` replacing existing <br>
+`CREATE AGGREGATE` replacing existing | | |
+
+|`ALTER` |`ALL ROLES` |`ALTER ROLE` on any role | | |
+
+|`ALTER` |`ROLE` |`ALTER ROLE` | | |
+
+|`DROP` |`ALL KEYSPACES` |`DROP KEYSPACE` <br> `DROP TABLE` in any
+keyspace | | |
+
+|`DROP` |`KEYSPACE` |`DROP TABLE` in specified keyspace | | |
+
+|`DROP` |`TABLE` |`DROP TABLE` | | |
+
+|`DROP` |`ALL FUNCTIONS` |`DROP FUNCTION` in any keyspace <br>
+`DROP AGGREGATE` in any existing | | |
+
+|`DROP` |`ALL FUNCTIONS IN KEYSPACE` |`DROP FUNCTION` in keyspace <br>
+`DROP AGGREGATE` in existing | | |
+
+|`DROP` |`FUNCTION` |`DROP FUNCTION` | | |
+
+|`DROP` |`ALL ROLES` |`DROP ROLE` on any role | | |
+
+|`DROP` |`ROLE` |`DROP ROLE` | | |
+
+|`SELECT` |`ALL KEYSPACES` |`SELECT` on any table | | |
+
+|`SELECT` |`KEYSPACE` |`SELECT` on any table in keyspace | | |
+
+|`SELECT` |`TABLE` |`SELECT` on specified table | | |
+
+|`SELECT` |`ALL MBEANS` |Call getter methods on any mbean | | |
+
+|`SELECT` |`MBEANS` |Call getter methods on any mbean matching a
+wildcard pattern | | |
+
+|`SELECT` |`MBEAN` |Call getter methods on named mbean | | |
+
+|`MODIFY` |`ALL KEYSPACES` |`INSERT` on any table <br> `UPDATE` on any
+table <br> `DELETE` on any table <br> `TRUNCATE` on any table | | |
+
+|`MODIFY` |`KEYSPACE` |`INSERT` on any table in keyspace <br> `UPDATE`
+on any table in keyspace <br> `DELETE` on any table in keyspace <br>
+`TRUNCATE` on any table in keyspace |`MODIFY` |`TABLE` |`INSERT` <br>
+`UPDATE` <br> `DELETE` <br> `TRUNCATE`
+
+|`MODIFY` |`ALL MBEANS` |Call setter methods on any mbean | | |
+
+|`MODIFY` |`MBEANS` |Call setter methods on any mbean matching a
+wildcard pattern | | |
+
+|`MODIFY` |`MBEAN` |Call setter methods on named mbean | | |
+
+|`AUTHORIZE` |`ALL KEYSPACES` |`GRANT PERMISSION` on any table <br>
+`REVOKE PERMISSION` on any table | | |
+
+|`AUTHORIZE` |`KEYSPACE` |`GRANT PERMISSION` on table in keyspace <br>
+`REVOKE PERMISSION` on table in keyspace | | |
+
+|`AUTHORIZE` |`TABLE` |`GRANT PERMISSION` <br> `REVOKE PERMISSION` | | |
+
+|`AUTHORIZE` |`ALL FUNCTIONS` |`GRANT PERMISSION` on any function <br>
+`REVOKE PERMISSION` on any function | | |
+
+|`AUTHORIZE` |`ALL FUNCTIONS IN KEYSPACE` |`GRANT PERMISSION` in
+keyspace <br> `REVOKE PERMISSION` in keyspace | | |
+
+|`AUTHORIZE` |`ALL FUNCTIONS IN KEYSPACE` |`GRANT PERMISSION` in
+keyspace <br> `REVOKE PERMISSION` in keyspace | | |
+
+|`AUTHORIZE` |`FUNCTION` |`GRANT PERMISSION` <br> `REVOKE PERMISSION` |
+| |
+
+|`AUTHORIZE` |`ALL MBEANS` |`GRANT PERMISSION` on any mbean <br>
+`REVOKE PERMISSION` on any mbean | | |
+
+|`AUTHORIZE` |`MBEANS` |`GRANT PERMISSION` on any mbean matching a
+wildcard pattern <br> `REVOKE PERMISSION` on any mbean matching a
+wildcard pattern | | |
+
+|`AUTHORIZE` |`MBEAN` |`GRANT PERMISSION` on named mbean <br>
+`REVOKE PERMISSION` on named mbean | | |
+
+|`AUTHORIZE` |`ALL ROLES` |`GRANT ROLE` grant any role <br>
+`REVOKE ROLE` revoke any role | | |
+
+|`AUTHORIZE` |`ROLES` |`GRANT ROLE` grant role <br> `REVOKE ROLE` revoke
+role | | |
+
+|`DESCRIBE` |`ALL ROLES` |`LIST ROLES` all roles or only roles granted
+to another, specified role | | |
+
+|`DESCRIBE` |@ALL MBEANS |Retrieve metadata about any mbean from the
+platform’s MBeanServer | | |
+
+|`DESCRIBE` |@MBEANS |Retrieve metadata about any mbean matching a
+wildcard patter from the platform’s MBeanServer | | |
+
+|`DESCRIBE` |@MBEAN |Retrieve metadata about a named mbean from the
+platform’s MBeanServer | | |
+
+|`EXECUTE` |`ALL FUNCTIONS` |`SELECT`, `INSERT`, `UPDATE` using any
+function <br> use of any function in `CREATE AGGREGATE` | | |
+
+|`EXECUTE` |`ALL FUNCTIONS IN KEYSPACE` |`SELECT`, `INSERT`, `UPDATE`
+using any function in keyspace <br> use of any function in keyspace in
+`CREATE AGGREGATE` | | |
+
+|`EXECUTE` |`FUNCTION` |`SELECT`, `INSERT`, `UPDATE` using function <br>
+use of function in `CREATE AGGREGATE` | | |
+
+|`EXECUTE` |`ALL MBEANS` |Execute operations on any mbean | | |
+
+|`EXECUTE` |`MBEANS` |Execute operations on any mbean matching a
+wildcard pattern | | |
+
+|`EXECUTE` |`MBEAN` |Execute operations on named mbean | | |
+|===
+
+[[grantPermissionsStmt]]
+==== GRANT PERMISSION
+
+_Syntax:_
+
+bc(syntax).. +
+::= GRANT ( ALL ( PERMISSIONS )? | ( PERMISSION )? ) ON TO
+
+::= CREATE | ALTER | DROP | SELECT | MODIFY | AUTHORIZE | DESRIBE |
+EXECUTE
+
+::= ALL KEYSPACES +
+| KEYSPACE +
+| ( TABLE )? +
+| ALL ROLES +
+| ROLE +
+| ALL FUNCTIONS ( IN KEYSPACE )? +
+| FUNCTION +
+| ALL MBEANS +
+| ( MBEAN | MBEANS ) +
+p.
+
+_Sample:_
+
+bc(sample). +
+GRANT SELECT ON ALL KEYSPACES TO data_reader;
+
+This gives any user with the role `data_reader` permission to execute
+`SELECT` statements on any table across all keyspaces
+
+bc(sample). +
+GRANT MODIFY ON KEYSPACE keyspace1 TO data_writer;
+
+This give any user with the role `data_writer` permission to perform
+`UPDATE`, `INSERT`, `UPDATE`, `DELETE` and `TRUNCATE` queries on all
+tables in the `keyspace1` keyspace
+
+bc(sample). +
+GRANT DROP ON keyspace1.table1 TO schema_owner;
+
+This gives any user with the `schema_owner` role permissions to `DROP`
+`keyspace1.table1`.
+
+bc(sample). +
+GRANT EXECUTE ON FUNCTION keyspace1.user_function( int ) TO
+report_writer;
+
+This grants any user with the `report_writer` role permission to execute
+`SELECT`, `INSERT` and `UPDATE` queries which use the function
+`keyspace1.user_function( int )`
+
+bc(sample). +
+GRANT DESCRIBE ON ALL ROLES TO role_admin;
+
+This grants any user with the `role_admin` role permission to view any
+and all roles in the system with a `LIST ROLES` statement
+
+[[grantAll]]
+===== GRANT ALL
+
+When the `GRANT ALL` form is used, the appropriate set of permissions is
+determined automatically based on the target resource.
+
+[[autoGrantPermissions]]
+===== Automatic Granting
+
+When a resource is created, via a `CREATE KEYSPACE`, `CREATE TABLE`,
+`CREATE FUNCTION`, `CREATE AGGREGATE` or `CREATE ROLE` statement, the
+creator (the role the database user who issues the statement is
+identified as), is automatically granted all applicable permissions on
+the new resource.
+
+[[revokePermissionsStmt]]
+==== REVOKE PERMISSION
+
+_Syntax:_
+
+bc(syntax).. +
+::= REVOKE ( ALL ( PERMISSIONS )? | ( PERMISSION )? ) ON FROM
+
+::= CREATE | ALTER | DROP | SELECT | MODIFY | AUTHORIZE | DESRIBE |
+EXECUTE
+
+::= ALL KEYSPACES +
+| KEYSPACE +
+| ( TABLE )? +
+| ALL ROLES +
+| ROLE +
+| ALL FUNCTIONS ( IN KEYSPACE )? +
+| FUNCTION +
+| ALL MBEANS +
+| ( MBEAN | MBEANS ) +
+p.
+
+_Sample:_
+
+bc(sample).. +
+REVOKE SELECT ON ALL KEYSPACES FROM data_reader; +
+REVOKE MODIFY ON KEYSPACE keyspace1 FROM data_writer; +
+REVOKE DROP ON keyspace1.table1 FROM schema_owner; +
+REVOKE EXECUTE ON FUNCTION keyspace1.user_function( int ) FROM
+report_writer; +
+REVOKE DESCRIBE ON ALL ROLES FROM role_admin; +
+p.
+
+[[listPermissionsStmt]]
+===== LIST PERMISSIONS
+
+_Syntax:_
+
+bc(syntax).. +
+::= LIST ( ALL ( PERMISSIONS )? | ) +
+( ON )? +
+( OF ( NORECURSIVE )? )?
+
+::= ALL KEYSPACES +
+| KEYSPACE +
+| ( TABLE )? +
+| ALL ROLES +
+| ROLE +
+| ALL FUNCTIONS ( IN KEYSPACE )? +
+| FUNCTION +
+| ALL MBEANS +
+| ( MBEAN | MBEANS ) +
+p.
+
+_Sample:_
+
+bc(sample). +
+LIST ALL PERMISSIONS OF alice;
+
+Show all permissions granted to `alice`, including those acquired
+transitively from any other roles.
+
+bc(sample). +
+LIST ALL PERMISSIONS ON keyspace1.table1 OF bob;
+
+Show all permissions on `keyspace1.table1` granted to `bob`, including
+those acquired transitively from any other roles. This also includes any
+permissions higher up the resource hierarchy which can be applied to
+`keyspace1.table1`. For example, should `bob` have `ALTER` permission on
+`keyspace1`, that would be included in the results of this query. Adding
+the `NORECURSIVE` switch restricts the results to only those permissions
+which were directly granted to `bob` or one of `bob`’s roles.
+
+bc(sample). +
+LIST SELECT PERMISSIONS OF carlos;
+
+Show any permissions granted to `carlos` or any of `carlos`’s roles,
+limited to `SELECT` permissions on any resource.
+
+[[types]]
+=== Data Types
+
+CQL supports a rich set of data types for columns defined in a table,
+including collection types. On top of those native +
+and collection types, users can also provide custom types (through a
+JAVA class extending `AbstractType` loadable by +
+Cassandra). The syntax of types is thus:
+
+bc(syntax).. +
+::= +
+| +
+| +
+| // Used for custom types. The fully-qualified name of a JAVA class
+
+::= ascii +
+| bigint +
+| blob +
+| boolean +
+| counter +
+| date +
+| decimal +
+| double +
+| float +
+| inet +
+| int +
+| smallint +
+| text +
+| time +
+| timestamp +
+| timeuuid +
+| tinyint +
+| uuid +
+| varchar +
+| varint
+
+::= list `<' `>' +
+| set `<' `>' +
+| map `<' `,' `>' +
+::= tuple `<' (`,' )* `>' +
+p. Note that the native types are keywords and as such are
+case-insensitive. They are however not reserved ones.
+
+The following table gives additional informations on the native data
+types, and on which kind of link:#constants[constants] each type
+supports:
+
+[cols=",,",options="header",]
+|===
+|type |constants supported |description
+|`ascii` |strings |ASCII character string
+
+|`bigint` |integers |64-bit signed long
+
+|`blob` |blobs |Arbitrary bytes (no validation)
+
+|`boolean` |booleans |true or false
+
+|`counter` |integers |Counter column (64-bit signed value). See
+link:#counters[Counters] for details
+
+|`date` |integers, strings |A date (with no corresponding time value).
+See link:#usingdates[Working with dates] below for more information.
+
+|`decimal` |integers, floats |Variable-precision decimal
+
+|`double` |integers |64-bit IEEE-754 floating point
+
+|`float` |integers, floats |32-bit IEEE-754 floating point
+
+|`inet` |strings |An IP address. It can be either 4 bytes long (IPv4) or
+16 bytes long (IPv6). There is no `inet` constant, IP address should be
+inputed as strings
+
+|`int` |integers |32-bit signed int
+
+|`smallint` |integers |16-bit signed int
+
+|`text` |strings |UTF8 encoded string
+
+|`time` |integers, strings |A time with nanosecond precision. See
+link:#usingtime[Working with time] below for more information.
+
+|`timestamp` |integers, strings |A timestamp. Strings constant are allow
+to input timestamps as dates, see link:#usingtimestamps[Working with
+timestamps] below for more information.
+
+|`timeuuid` |uuids |Type 1 UUID. This is generally used as a
+``conflict-free'' timestamp. Also see the link:#timeuuidFun[functions on
+Timeuuid]
+
+|`tinyint` |integers |8-bit signed int
+
+|`uuid` |uuids |Type 1 or type 4 UUID
+
+|`varchar` |strings |UTF8 encoded string
+
+|`varint` |integers |Arbitrary-precision integer
+|===
+
+For more information on how to use the collection types, see the
+link:#collections[Working with collections] section below.
+
+[[usingtimestamps]]
+==== Working with timestamps
+
+Values of the `timestamp` type are encoded as 64-bit signed integers
+representing a number of milliseconds since the standard base time known
+as ``the epoch'': January 1 1970 at 00:00:00 GMT.
+
+Timestamp can be input in CQL as simple long integers, giving the number
+of milliseconds since the epoch, as defined above.
+
+They can also be input as string literals in any of the following ISO
+8601 formats, each representing the time and date Mar 2, 2011, at
+04:05:00 AM, GMT.:
+
+* `2011-02-03 04:05+0000`
+* `2011-02-03 04:05:00+0000`
+* `2011-02-03 04:05:00.000+0000`
+* `2011-02-03T04:05+0000`
+* `2011-02-03T04:05:00+0000`
+* `2011-02-03T04:05:00.000+0000`
+
+The `+0000` above is an RFC 822 4-digit time zone specification; `+0000`
+refers to GMT. US Pacific Standard Time is `-0800`. The time zone may be
+omitted if desired— the date will be interpreted as being in the time
+zone under which the coordinating Cassandra node is configured.
+
+* `2011-02-03 04:05`
+* `2011-02-03 04:05:00`
+* `2011-02-03 04:05:00.000`
+* `2011-02-03T04:05`
+* `2011-02-03T04:05:00`
+* `2011-02-03T04:05:00.000`
+
+There are clear difficulties inherent in relying on the time zone
+configuration being as expected, though, so it is recommended that the
+time zone always be specified for timestamps when feasible.
+
+The time of day may also be omitted, if the date is the only piece that
+matters:
+
+* `2011-02-03`
+* `2011-02-03+0000`
+
+In that case, the time of day will default to 00:00:00, in the specified
+or default time zone.
+
+[[usingdates]]
+==== Working with dates
+
+Values of the `date` type are encoded as 32-bit unsigned integers
+representing a number of days with ``the epoch'' at the center of the
+range (2^31). Epoch is January 1st, 1970
+
+A date can be input in CQL as an unsigned integer as defined above.
+
+They can also be input as string literals in the following format:
+
+* `2014-01-01`
+
+[[usingtime]]
+==== Working with time
+
+Values of the `time` type are encoded as 64-bit signed integers
+representing the number of nanoseconds since midnight.
+
+A time can be input in CQL as simple long integers, giving the number of
+nanoseconds since midnight.
+
+They can also be input as string literals in any of the following
+formats:
+
+* `08:12:54`
+* `08:12:54.123`
+* `08:12:54.123456`
+* `08:12:54.123456789`
+
+==== Counters
+
+The `counter` type is used to define _counter columns_. A counter column
+is a column whose value is a 64-bit signed integer and on which 2
+operations are supported: incrementation and decrementation (see
+link:#updateStmt[`UPDATE`] for syntax). Note the value of a counter
+cannot be set. A counter doesn’t exist until first
+incremented/decremented, and the first incrementation/decrementation is
+made as if the previous value was 0. Deletion of counter columns is
+supported but have some limitations (see the
+http://wiki.apache.org/cassandra/Counters[Cassandra Wiki] for more
+information).
+
+The use of the counter type is limited in the following way:
+
+* It cannot be used for column that is part of the `PRIMARY KEY` of a
+table.
+* A table that contains a counter can only contain counters. In other
+words, either all the columns of a table outside the `PRIMARY KEY` have
+the counter type, or none of them have it.
+
+[[collections]]
+==== Working with collections
+
+===== Noteworthy characteristics
+
+Collections are meant for storing/denormalizing relatively small amount
+of data. They work well for things like ``the phone numbers of a given
+user'', ``labels applied to an email'', etc. But when items are expected
+to grow unbounded (``all the messages sent by a given user'', ``events
+registered by a sensor'', …), then collections are not appropriate
+anymore and a specific table (with clustering columns) should be used.
+Concretely, collections have the following limitations:
+
+* Collections are always read in their entirety (and reading one is not
+paged internally).
+* Collections cannot have more than 65535 elements. More precisely,
+while it may be possible to insert more than 65535 elements, it is not
+possible to read more than the 65535 first elements (see
+https://issues.apache.org/jira/browse/CASSANDRA-5428[CASSANDRA-5428] for
+details).
+* While insertion operations on sets and maps never incur a
+read-before-write internally, some operations on lists do (see the
+section on lists below for details). It is thus advised to prefer sets
+over lists when possible.
+
+Please note that while some of those limitations may or may not be
+loosen in the future, the general rule that collections are for
+denormalizing small amount of data is meant to stay.
+
+[[map]]
+===== Maps
+
+A `map` is a link:#types[typed] set of key-value pairs, where keys are
+unique. Furthermore, note that the map are internally sorted by their
+keys and will thus always be returned in that order. To create a column
+of type `map`, use the `map` keyword suffixed with comma-separated key
+and value types, enclosed in angle brackets. For example:
+
+bc(sample). +
+CREATE TABLE users ( +
+id text PRIMARY KEY, +
+given text, +
+surname text, +
+favs map<text, text> // A map of text keys, and text values +
+)
+
+Writing `map` data is accomplished with a JSON-inspired syntax. To write
+a record using `INSERT`, specify the entire map as a JSON-style
+associative array. _Note: This form will always replace the entire map._
+
+bc(sample). +
+// Inserting (or Updating) +
+INSERT INTO users (id, given, surname, favs) +
+VALUES (`jsmith', `John', `Smith', \{ `fruit' : `apple', `band' :
+`Beatles' })
+
+Adding or updating key-values of a (potentially) existing map can be
+accomplished either by subscripting the map column in an `UPDATE`
+statement or by adding a new map literal:
+
+bc(sample). +
+// Updating (or inserting) +
+UPDATE users SET favs[`author'] = `Ed Poe' WHERE id = `jsmith' +
+UPDATE users SET favs = favs + \{ `movie' : `Cassablanca' } WHERE id =
+`jsmith'
+
+Note that TTLs are allowed for both `INSERT` and `UPDATE`, but in both
+case the TTL set only apply to the newly inserted/updated _values_. In
+other words,
+
+bc(sample). +
+// Updating (or inserting) +
+UPDATE users USING TTL 10 SET favs[`color'] = `green' WHERE id =
+`jsmith'
+
+will only apply the TTL to the `{ 'color' : 'green' }` record, the rest
+of the map remaining unaffected.
+
+Deleting a map record is done with:
+
+bc(sample). +
+DELETE favs[`author'] FROM users WHERE id = `jsmith'
+
+[[set]]
+===== Sets
+
+A `set` is a link:#types[typed] collection of unique values. Sets are
+ordered by their values. To create a column of type `set`, use the `set`
+keyword suffixed with the value type enclosed in angle brackets. For
+example:
+
+bc(sample). +
+CREATE TABLE images ( +
+name text PRIMARY KEY, +
+owner text, +
+date timestamp, +
+tags set +
+);
+
+Writing a `set` is accomplished by comma separating the set values, and
+enclosing them in curly braces. _Note: An `INSERT` will always replace
+the entire set._
+
+bc(sample). +
+INSERT INTO images (name, owner, date, tags) +
+VALUES (`cat.jpg', `jsmith', `now', \{ `kitten', `cat', `pet' });
+
+Adding and removing values of a set can be accomplished with an `UPDATE`
+by adding/removing new set values to an existing `set` column.
+
+bc(sample). +
+UPDATE images SET tags = tags + \{ `cute', `cuddly' } WHERE name =
+`cat.jpg'; +
+UPDATE images SET tags = tags - \{ `lame' } WHERE name = `cat.jpg';
+
+As with link:#map[maps], TTLs if used only apply to the newly
+inserted/updated _values_.
+
+[[list]]
+===== Lists
+
+A `list` is a link:#types[typed] collection of non-unique values where
+elements are ordered by there position in the list. To create a column
+of type `list`, use the `list` keyword suffixed with the value type
+enclosed in angle brackets. For example:
+
+bc(sample). +
+CREATE TABLE plays ( +
+id text PRIMARY KEY, +
+game text, +
+players int, +
+scores list +
+)
+
+Do note that as explained below, lists have some limitations and
+performance considerations to take into account, and it is advised to
+prefer link:#set[sets] over lists when this is possible.
+
+Writing `list` data is accomplished with a JSON-style syntax. To write a
+record using `INSERT`, specify the entire list as a JSON array. _Note:
+An `INSERT` will always replace the entire list._
+
+bc(sample). +
+INSERT INTO plays (id, game, players, scores) +
+VALUES (`123-afde', `quake', 3, [17, 4, 2]);
+
+Adding (appending or prepending) values to a list can be accomplished by
+adding a new JSON-style array to an existing `list` column.
+
+bc(sample). +
+UPDATE plays SET players = 5, scores = scores + [ 14, 21 ] WHERE id =
+`123-afde'; +
+UPDATE plays SET players = 5, scores = [ 12 ] + scores WHERE id =
+`123-afde';
+
+It should be noted that append and prepend are not idempotent
+operations. This means that if during an append or a prepend the
+operation timeout, it is not always safe to retry the operation (as this
+could result in the record appended or prepended twice).
+
+Lists also provides the following operation: setting an element by its
+position in the list, removing an element by its position in the list
+and remove all the occurrence of a given value in the list. _However,
+and contrarily to all the other collection operations, these three
+operations induce an internal read before the update, and will thus
+typically have slower performance characteristics_. Those operations
+have the following syntax:
+
+bc(sample). +
+UPDATE plays SET scores[1] = 7 WHERE id = `123-afde'; // sets the 2nd
+element of scores to 7 (raises an error is scores has less than 2
+elements) +
+DELETE scores[1] FROM plays WHERE id = `123-afde'; // deletes the 2nd
+element of scores (raises an error is scores has less than 2 elements) +
+UPDATE plays SET scores = scores - [ 12, 21 ] WHERE id = `123-afde'; //
+removes all occurrences of 12 and 21 from scores
+
+As with link:#map[maps], TTLs if used only apply to the newly
+inserted/updated _values_.
+
+=== Functions
+
+CQL3 distinguishes between built-in functions (so called `native
+functions') and link:#udfs[user-defined functions]. CQL3 includes
+several native functions, described below:
+
+[[castFun]]
+==== Cast
+
+The `cast` function can be used to converts one native datatype to
+another.
+
+The following table describes the conversions supported by the `cast`
+function. Cassandra will silently ignore any cast converting a datatype
+into its own datatype.
+
+[cols=",",options="header",]
+|===
+|from |to
+|`ascii` |`text`, `varchar`
+
+|`bigint` |`tinyint`, `smallint`, `int`, `float`, `double`, `decimal`,
+`varint`, `text`, `varchar`
+
+|`boolean` |`text`, `varchar`
+
+|`counter` |`tinyint`, `smallint`, `int`, `bigint`, `float`, `double`,
+`decimal`, `varint`, `text`, `varchar`
+
+|`date` |`timestamp`
+
+|`decimal` |`tinyint`, `smallint`, `int`, `bigint`, `float`, `double`,
+`varint`, `text`, `varchar`
+
+|`double` |`tinyint`, `smallint`, `int`, `bigint`, `float`, `decimal`,
+`varint`, `text`, `varchar`
+
+|`float` |`tinyint`, `smallint`, `int`, `bigint`, `double`, `decimal`,
+`varint`, `text`, `varchar`
+
+|`inet` |`text`, `varchar`
+
+|`int` |`tinyint`, `smallint`, `bigint`, `float`, `double`, `decimal`,
+`varint`, `text`, `varchar`
+
+|`smallint` |`tinyint`, `int`, `bigint`, `float`, `double`, `decimal`,
+`varint`, `text`, `varchar`
+
+|`time` |`text`, `varchar`
+
+|`timestamp` |`date`, `text`, `varchar`
+
+|`timeuuid` |`timestamp`, `date`, `text`, `varchar`
+
+|`tinyint` |`tinyint`, `smallint`, `int`, `bigint`, `float`, `double`,
+`decimal`, `varint`, `text`, `varchar`
+
+|`uuid` |`text`, `varchar`
+
+|`varint` |`tinyint`, `smallint`, `int`, `bigint`, `float`, `double`,
+`decimal`, `text`, `varchar`
+|===
+
+The conversions rely strictly on Java’s semantics. For example, the
+double value 1 will be converted to the text value `1.0'.
+
+bc(sample). +
+SELECT avg(cast(count as double)) FROM myTable
+
+[[tokenFun]]
+==== Token
+
+The `token` function allows to compute the token for a given partition
+key. The exact signature of the token function depends on the table
+concerned and of the partitioner used by the cluster.
+
+The type of the arguments of the `token` depend on the type of the
+partition key columns. The return type depend on the partitioner in use:
+
+* For Murmur3Partitioner, the return type is `bigint`.
+* For RandomPartitioner, the return type is `varint`.
+* For ByteOrderedPartitioner, the return type is `blob`.
+
+For instance, in a cluster using the default Murmur3Partitioner, if a
+table is defined by
+
+bc(sample). +
+CREATE TABLE users ( +
+userid text PRIMARY KEY, +
+username text, +
+… +
+)
+
+then the `token` function will take a single argument of type `text` (in
+that case, the partition key is `userid` (there is no clustering columns
+so the partition key is the same than the primary key)), and the return
+type will be `bigint`.
+
+[[uuidFun]]
+==== Uuid
+
+The `uuid` function takes no parameters and generates a random type 4
+uuid suitable for use in INSERT or SET statements.
+
+[[timeuuidFun]]
+==== Timeuuid functions
+
+===== `now`
+
+The `now` function takes no arguments and generates, on the coordinator
+node, a new unique timeuuid (at the time where the statement using it is
+executed). Note that this method is useful for insertion but is largely
+non-sensical in `WHERE` clauses. For instance, a query of the form
+
+bc(sample). +
+SELECT * FROM myTable WHERE t = now()
+
+will never return any result by design, since the value returned by
+`now()` is guaranteed to be unique.
+
+===== `minTimeuuid` and `maxTimeuuid`
+
+The `minTimeuuid` (resp. `maxTimeuuid`) function takes a `timestamp`
+value `t` (which can be link:#usingtimestamps[either a timestamp or a
+date string] ) and return a _fake_ `timeuuid` corresponding to the
+_smallest_ (resp. _biggest_) possible `timeuuid` having for timestamp
+`t`. So for instance:
+
+bc(sample). +
+SELECT * FROM myTable WHERE t > maxTimeuuid(`2013-01-01 00:05+0000') AND
+t < minTimeuuid(`2013-02-02 10:00+0000')
+
+will select all rows where the `timeuuid` column `t` is strictly older
+than `2013-01-01 00:05+0000' but strictly younger than `2013-02-02
+10:00+0000'. Please note that
+`t >= maxTimeuuid('2013-01-01 00:05+0000')` would still _not_ select a
+`timeuuid` generated exactly at `2013-01-01 00:05+0000' and is
+essentially equivalent to `t > maxTimeuuid('2013-01-01 00:05+0000')`.
+
+_Warning_: We called the values generated by `minTimeuuid` and
+`maxTimeuuid` _fake_ UUID because they do no respect the Time-Based UUID
+generation process specified by the
+http://www.ietf.org/rfc/rfc4122.txt[RFC 4122]. In particular, the value
+returned by these 2 methods will not be unique. This means you should
+only use those methods for querying (as in the example above). Inserting
+the result of those methods is almost certainly _a bad idea_.
+
+[[timeFun]]
+==== Time conversion functions
+
+A number of functions are provided to ``convert'' a `timeuuid`, a
+`timestamp` or a `date` into another `native` type.
+
+[cols=",,",options="header",]
+|===
+|function name |input type |description
+|`toDate` |`timeuuid` |Converts the `timeuuid` argument into a `date`
+type
+
+|`toDate` |`timestamp` |Converts the `timestamp` argument into a `date`
+type
+
+|`toTimestamp` |`timeuuid` |Converts the `timeuuid` argument into a
+`timestamp` type
+
+|`toTimestamp` |`date` |Converts the `date` argument into a `timestamp`
+type
+
+|`toUnixTimestamp` |`timeuuid` |Converts the `timeuuid` argument into a
+`bigInt` raw value
+
+|`toUnixTimestamp` |`timestamp` |Converts the `timestamp` argument into
+a `bigInt` raw value
+
+|`toUnixTimestamp` |`date` |Converts the `date` argument into a `bigInt`
+raw value
+
+|`dateOf` |`timeuuid` |Similar to `toTimestamp(timeuuid)` (DEPRECATED)
+
+|`unixTimestampOf` |`timeuuid` |Similar to `toUnixTimestamp(timeuuid)`
+(DEPRECATED)
+|===
+
+[[blobFun]]
+==== Blob conversion functions
+
+A number of functions are provided to ``convert'' the native types into
+binary data (`blob`). For every `<native-type>` `type` supported by CQL3
+(a notable exceptions is `blob`, for obvious reasons), the function
+`typeAsBlob` takes a argument of type `type` and return it as a `blob`.
+Conversely, the function `blobAsType` takes a 64-bit `blob` argument and
+convert it to a `bigint` value. And so for instance, `bigintAsBlob(3)`
+is `0x0000000000000003` and `blobAsBigint(0x0000000000000003)` is `3`.
+
+=== Aggregates
+
+Aggregate functions work on a set of rows. They receive values for each
+row and returns one value for the whole set. +
+If `normal` columns, `scalar functions`, `UDT` fields, `writetime` or
+`ttl` are selected together with aggregate functions, the values
+returned for them will be the ones of the first row matching the query.
+
+CQL3 distinguishes between built-in aggregates (so called `native
+aggregates') and link:#udas[user-defined aggregates]. CQL3 includes
+several native aggregates, described below:
+
+[[countFct]]
+==== Count
+
+The `count` function can be used to count the rows returned by a query.
+Example:
+
+bc(sample). +
+SELECT COUNT (*) FROM plays; +
+SELECT COUNT (1) FROM plays;
+
+It also can be used to count the non null value of a given column.
+Example:
+
+bc(sample). +
+SELECT COUNT (scores) FROM plays;
+
+[[maxMinFcts]]
+==== Max and Min
+
+The `max` and `min` functions can be used to compute the maximum and the
+minimum value returned by a query for a given column.
+
+bc(sample). +
+SELECT MIN (players), MAX (players) FROM plays WHERE game = `quake';
+
+[[sumFct]]
+==== Sum
+
+The `sum` function can be used to sum up all the values returned by a
+query for a given column.
+
+bc(sample). +
+SELECT SUM (players) FROM plays;
+
+[[avgFct]]
+==== Avg
+
+The `avg` function can be used to compute the average of all the values
+returned by a query for a given column.
+
+bc(sample). +
+SELECT AVG (players) FROM plays;
+
+[[udfs]]
+=== User-Defined Functions
+
+User-defined functions allow execution of user-provided code in
+Cassandra. By default, Cassandra supports defining functions in _Java_
+and _JavaScript_. Support for other JSR 223 compliant scripting
+languages (such as Python, Ruby, and Scala) has been removed in 3.0.11.
+
+UDFs are part of the Cassandra schema. As such, they are automatically
+propagated to all nodes in the cluster.
+
+UDFs can be _overloaded_ - i.e. multiple UDFs with different argument
+types but the same function name. Example:
+
+bc(sample). +
+CREATE FUNCTION sample ( arg int ) …; +
+CREATE FUNCTION sample ( arg text ) …;
+
+User-defined functions are susceptible to all of the normal problems
+with the chosen programming language. Accordingly, implementations
+should be safe against null pointer exceptions, illegal arguments, or
+any other potential source of exceptions. An exception during function
+execution will result in the entire statement failing.
+
+It is valid to use _complex_ types like collections, tuple types and
+user-defined types as argument and return types. Tuple types and
+user-defined types are handled by the conversion functions of the
+DataStax Java Driver. Please see the documentation of the Java Driver
+for details on handling tuple types and user-defined types.
+
+Arguments for functions can be literals or terms. Prepared statement
+placeholders can be used, too.
+
+Note that you can use the double-quoted string syntax to enclose the UDF
+source code. For example:
+
+bc(sample).. +
+CREATE FUNCTION some_function ( arg int ) +
+RETURNS NULL ON NULL INPUT +
+RETURNS int +
+LANGUAGE java +
+AS $$ return arg; $$;
+
+SELECT some_function(column) FROM atable …; +
+UPDATE atable SET col = some_function(?) …; +
+p.
+
+bc(sample). +
+CREATE TYPE custom_type (txt text, i int); +
+CREATE FUNCTION fct_using_udt ( udtarg frozen ) +
+RETURNS NULL ON NULL INPUT +
+RETURNS text +
+LANGUAGE java +
+AS $$ return udtarg.getString(``txt''); $$;
+
+User-defined functions can be used in link:#selectStmt[`SELECT`],
+link:#insertStmt[`INSERT`] and link:#updateStmt[`UPDATE`] statements.
+
+The implicitly available `udfContext` field (or binding for script UDFs)
+provides the neccessary functionality to create new UDT and tuple
+values.
+
+bc(sample). +
+CREATE TYPE custom_type (txt text, i int); +
+CREATE FUNCTION fct_using_udt ( somearg int ) +
+RETURNS NULL ON NULL INPUT +
+RETURNS custom_type +
+LANGUAGE java +
+AS $$ +
+UDTValue udt = udfContext.newReturnUDTValue(); +
+udt.setString(``txt'', ``some string''); +
+udt.setInt(``i'', 42); +
+return udt; +
+$$;
+
+The definition of the `UDFContext` interface can be found in the Apache
+Cassandra source code for
+`org.apache.cassandra.cql3.functions.UDFContext`.
+
+bc(sample). +
+public interface UDFContext +
+\{ +
+UDTValue newArgUDTValue(String argName); +
+UDTValue newArgUDTValue(int argNum); +
+UDTValue newReturnUDTValue(); +
+UDTValue newUDTValue(String udtName); +
+TupleValue newArgTupleValue(String argName); +
+TupleValue newArgTupleValue(int argNum); +
+TupleValue newReturnTupleValue(); +
+TupleValue newTupleValue(String cqlDefinition); +
+}
+
+Java UDFs already have some imports for common interfaces and classes
+defined. These imports are: +
+Please note, that these convenience imports are not available for script
+UDFs.
+
+bc(sample). +
+import java.nio.ByteBuffer; +
+import java.util.List; +
+import java.util.Map; +
+import java.util.Set; +
+import org.apache.cassandra.cql3.functions.UDFContext; +
+import com.datastax.driver.core.TypeCodec; +
+import com.datastax.driver.core.TupleValue; +
+import com.datastax.driver.core.UDTValue;
+
+See link:#createFunctionStmt[`CREATE FUNCTION`] and
+link:#dropFunctionStmt[`DROP FUNCTION`].
+
+[[udas]]
+=== User-Defined Aggregates
+
+User-defined aggregates allow creation of custom aggregate functions
+using link:#udfs[UDFs]. Common examples of aggregate functions are
+_count_, _min_, and _max_.
+
+Each aggregate requires an _initial state_ (`INITCOND`, which defaults
+to `null`) of type `STYPE`. The first argument of the state function
+must have type `STYPE`. The remaining arguments of the state function
+must match the types of the user-defined aggregate arguments. The state
+function is called once for each row, and the value returned by the
+state function becomes the new state. After all rows are processed, the
+optional `FINALFUNC` is executed with last state value as its argument.
+
+`STYPE` is mandatory in order to be able to distinguish possibly
+overloaded versions of the state and/or final function (since the
+overload can appear after creation of the aggregate).
+
+User-defined aggregates can be used in link:#selectStmt[`SELECT`]
+statement.
+
+A complete working example for user-defined aggregates (assuming that a
+keyspace has been selected using the link:#useStmt[`USE`] statement):
+
+bc(sample).. +
+CREATE OR REPLACE FUNCTION averageState ( state tuple<int,bigint>, val
+int ) +
+CALLED ON NULL INPUT +
+RETURNS tuple<int,bigint> +
+LANGUAGE java +
+AS ’ +
+if (val != null) \{ +
+state.setInt(0, state.getInt(0)+1); +
+state.setLong(1, state.getLong(1)+val.intValue()); +
+} +
+return state; +
+’;
+
+CREATE OR REPLACE FUNCTION averageFinal ( state tuple<int,bigint> ) +
+CALLED ON NULL INPUT +
+RETURNS double +
+LANGUAGE java +
+AS ’ +
+double r = 0; +
+if (state.getInt(0) == 0) return null; +
+r = state.getLong(1); +
+r /= state.getInt(0); +
+return Double.valueOf®; +
+’;
+
+CREATE OR REPLACE AGGREGATE average ( int ) +
+SFUNC averageState +
+STYPE tuple<int,bigint> +
+FINALFUNC averageFinal +
+INITCOND (0, 0);
+
+CREATE TABLE atable ( +
+pk int PRIMARY KEY, +
+val int); +
+INSERT INTO atable (pk, val) VALUES (1,1); +
+INSERT INTO atable (pk, val) VALUES (2,2); +
+INSERT INTO atable (pk, val) VALUES (3,3); +
+INSERT INTO atable (pk, val) VALUES (4,4); +
+SELECT average(val) FROM atable; +
+p.
+
+See link:#createAggregateStmt[`CREATE AGGREGATE`] and
+link:#dropAggregateStmt[`DROP AGGREGATE`].
+
+[[json]]
+=== JSON Support
+
+Cassandra 2.2 introduces JSON support to link:#selectStmt[`SELECT`] and
+link:#insertStmt[`INSERT`] statements. This support does not
+fundamentally alter the CQL API (for example, the schema is still
+enforced), it simply provides a convenient way to work with JSON
+documents.
+
+[[selectJson]]
+==== SELECT JSON
+
+With `SELECT` statements, the new `JSON` keyword can be used to return
+each row as a single `JSON` encoded map. The remainder of the `SELECT`
+statment behavior is the same.
+
+The result map keys are the same as the column names in a normal result
+set. For example, a statement like ```SELECT JSON a, ttl(b) FROM ...`''
+would result in a map with keys `"a"` and `"ttl(b)"`. However, this is
+one notable exception: for symmetry with `INSERT JSON` behavior,
+case-sensitive column names with upper-case letters will be surrounded
+with double quotes. For example, ```SELECT JSON myColumn FROM ...`''
+would result in a map key `"\"myColumn\""` (note the escaped quotes).
+
+The map values will `JSON`-encoded representations (as described below)
+of the result set values.
+
+[[insertJson]]
+==== INSERT JSON
+
+With `INSERT` statements, the new `JSON` keyword can be used to enable
+inserting a `JSON` encoded map as a single row. The format of the `JSON`
+map should generally match that returned by a `SELECT JSON` statement on
+the same table. In particular, case-sensitive column names should be
+surrounded with double quotes. For example, to insert into a table with
+two columns named ``myKey'' and ``value'', you would do the following:
+
+bc(sample). +
+INSERT INTO mytable JSON `\{``\''myKey\``'': 0, ``value'': 0}'
+
+Any columns which are ommitted from the `JSON` map will be defaulted to
+a `NULL` value (which will result in a tombstone being created).
+
+[[jsonEncoding]]
+==== JSON Encoding of Cassandra Data Types
+
+Where possible, Cassandra will represent and accept data types in their
+native `JSON` representation. Cassandra will also accept string
+representations matching the CQL literal format for all single-field
+types. For example, floats, ints, UUIDs, and dates can be represented by
+CQL literal strings. However, compound types, such as collections,
+tuples, and user-defined types must be represented by native `JSON`
+collections (maps and lists) or a JSON-encoded string representation of
+the collection.
+
+The following table describes the encodings that Cassandra will accept
+in `INSERT JSON` values (and `fromJson()` arguments) as well as the
+format Cassandra will use when returning data for `SELECT JSON`
+statements (and `fromJson()`):
+
+[cols=",,,",options="header",]
+|===
+|type |formats accepted |return format |notes
+|`ascii` |string |string |Uses JSON’s `\u` character escape
+
+|`bigint` |integer, string |integer |String must be valid 64 bit integer
+
+|`blob` |string |string |String should be 0x followed by an even number
+of hex digits
+
+|`boolean` |boolean, string |boolean |String must be ``true'' or
+``false''
+
+|`date` |string |string |Date in format `YYYY-MM-DD`, timezone UTC
+
+|`decimal` |integer, float, string |float |May exceed 32 or 64-bit
+IEEE-754 floating point precision in client-side decoder
+
+|`double` |integer, float, string |float |String must be valid integer
+or float
+
+|`float` |integer, float, string |float |String must be valid integer or
+float
+
+|`inet` |string |string |IPv4 or IPv6 address
+
+|`int` |integer, string |integer |String must be valid 32 bit integer
+
+|`list` |list, string |list |Uses JSON’s native list representation
+
+|`map` |map, string |map |Uses JSON’s native map representation
+
+|`smallint` |integer, string |integer |String must be valid 16 bit
+integer
+
+|`set` |list, string |list |Uses JSON’s native list representation
+
+|`text` |string |string |Uses JSON’s `\u` character escape
+
+|`time` |string |string |Time of day in format `HH-MM-SS[.fffffffff]`
+
+|`timestamp` |integer, string |string |A timestamp. Strings constant are
+allow to input timestamps as dates, see link:#usingdates[Working with
+dates] below for more information. Datestamps with format
+`YYYY-MM-DD HH:MM:SS.SSS` are returned.
+
+|`timeuuid` |string |string |Type 1 UUID. See link:#constants[Constants]
+for the UUID format
+
+|`tinyint` |integer, string |integer |String must be valid 8 bit integer
+
+|`tuple` |list, string |list |Uses JSON’s native list representation
+
+|`UDT` |map, string |map |Uses JSON’s native map representation with
+field names as keys
+
+|`uuid` |string |string |See link:#constants[Constants] for the UUID
+format
+
+|`varchar` |string |string |Uses JSON’s `\u` character escape
+
+|`varint` |integer, string |integer |Variable length; may overflow 32 or
+64 bit integers in client-side decoder
+|===
+
+[[fromJson]]
+==== The fromJson() Function
+
+The `fromJson()` function may be used similarly to `INSERT JSON`, but
+for a single column value. It may only be used in the `VALUES` clause of
+an `INSERT` statement or as one of the column values in an `UPDATE`,
+`DELETE`, or `SELECT` statement. For example, it cannot be used in the
+selection clause of a `SELECT` statement.
+
+[[toJson]]
+==== The toJson() Function
+
+The `toJson()` function may be used similarly to `SELECT JSON`, but for
+a single column value. It may only be used in the selection clause of a
+`SELECT` statement.
+
+[[appendixA]]
+=== Appendix A: CQL Keywords
+
+CQL distinguishes between _reserved_ and _non-reserved_ keywords.
+Reserved keywords cannot be used as identifier, they are truly reserved
+for the language (but one can enclose a reserved keyword by
+double-quotes to use it as an identifier). Non-reserved keywords however
+only have a specific meaning in certain context but can used as
+identifer otherwise. The only _raison d’être_ of these non-reserved
+keywords is convenience: some keyword are non-reserved when it was
+always easy for the parser to decide whether they were used as keywords
+or not.
+
+[cols=",",options="header",]
+|===
+|Keyword |Reserved?
+|`ADD` |yes
+|`AGGREGATE` |no
+|`ALL` |no
+|`ALLOW` |yes
+|`ALTER` |yes
+|`AND` |yes
+|`APPLY` |yes
+|`AS` |no
+|`ASC` |yes
+|`ASCII` |no
+|`AUTHORIZE` |yes
+|`BATCH` |yes
+|`BEGIN` |yes
+|`BIGINT` |no
+|`BLOB` |no
+|`BOOLEAN` |no
+|`BY` |yes
+|`CALLED` |no
+|`CAST` |no
+|`CLUSTERING` |no
+|`COLUMNFAMILY` |yes
+|`COMPACT` |no
+|`CONTAINS` |no
+|`COUNT` |no
+|`COUNTER` |no
+|`CREATE` |yes
+|`CUSTOM` |no
+|`DATE` |no
+|`DECIMAL` |no
+|`DEFAULT` |yes
+|`DELETE` |yes
+|`DESC` |yes
+|`DESCRIBE` |yes
+|`DISTINCT` |no
+|`DOUBLE` |no
+|`DROP` |yes
+|`DURATION` |no
+|`ENTRIES` |yes
+|`EXECUTE` |yes
+|`EXISTS` |no
+|`FILTERING` |no
+|`FINALFUNC` |no
+|`FLOAT` |no
+|`FROM` |yes
+|`FROZEN` |no
+|`FULL` |yes
+|`FUNCTION` |no
+|`FUNCTIONS` |no
+|`GRANT` |yes
+|`GROUP` |no
+|`IF` |yes
+|`IN` |yes
+|`INDEX` |yes
+|`INET` |no
+|`INFINITY` |yes
+|`INITCOND` |no
+|`INPUT` |no
+|`INSERT` |yes
+|`INT` |no
+|`INTO` |yes
+|`IS` |yes
+|`JSON` |no
+|`KEY` |no
+|`KEYS` |no
+|`KEYSPACE` |yes
+|`KEYSPACES` |no
+|`LANGUAGE` |no
+|`LIKE` |no
+|`LIMIT` |yes
+|`LIST` |no
+|`LOGIN` |no
+|`MAP` |no
+|`MATERIALIZED` |yes
+|`MBEAN` |yes
+|`MBEANS` |yes
+|`MODIFY` |yes
+|`NAN` |yes
+|`NOLOGIN` |no
+|`NORECURSIVE` |yes
+|`NOSUPERUSER` |no
+|`NOT` |yes
+|`NULL` |yes
+|`OF` |yes
+|`ON` |yes
+|`OPTIONS` |no
+|`OR` |yes
+|`ORDER` |yes
+|`PARTITION` |no
+|`PASSWORD` |no
+|`PER` |no
+|`PERMISSION` |no
+|`PERMISSIONS` |no
+|`PRIMARY` |yes
+|`RENAME` |yes
+|`REPLACE` |yes
+|`RETURNS` |no
+|`REVOKE` |yes
+|`ROLE` |no
+|`ROLES` |no
+|`SCHEMA` |yes
+|`SELECT` |yes
+|`SET` |yes
+|`SFUNC` |no
+|`SMALLINT` |no
+|`STATIC` |no
+|`STORAGE` |no
+|`STYPE` |no
+|`SUPERUSER` |no
+|`TABLE` |yes
+|`TEXT` |no
+|`TIME` |no
+|`TIMESTAMP` |no
+|`TIMEUUID` |no
+|`TINYINT` |no
+|`TO` |yes
+|`TOKEN` |yes
+|`TRIGGER` |no
+|`TRUNCATE` |yes
+|`TTL` |no
+|`TUPLE` |no
+|`TYPE` |no
+|`UNLOGGED` |yes
+|`UNSET` |yes
+|`UPDATE` |yes
+|`USE` |yes
+|`USER` |no
+|`USERS` |no
+|`USING` |yes
+|`UUID` |no
+|`VALUES` |no
+|`VARCHAR` |no
+|`VARINT` |no
+|`VIEW` |yes
+|`WHERE` |yes
+|`WITH` |yes
+|`WRITETIME` |no
+|===
+
+[[appendixB]]
+=== Appendix B: CQL Reserved Types
+
+The following type names are not currently used by CQL, but are reserved
+for potential future use. User-defined types may not use reserved type
+names as their name.
+
+[cols="",options="header",]
+|===
+|type
+|`bitstring`
+|`byte`
+|`complex`
+|`date`
+|`enum`
+|`interval`
+|`macaddr`
+|===
+
+=== Changes
+
+The following describes the changes in each version of CQL.
+
+==== 3.4.3
+
+* Support for `GROUP BY`. See link:#selectGroupBy[`<group-by>`] (see
+https://issues.apache.org/jira/browse/CASSANDRA-10707)[CASSANDRA-10707].
+
+==== 3.4.2
+
+* Support for selecting elements and slices of a collection
+(https://issues.apache.org/jira/browse/CASSANDRA-7396)[CASSANDRA-7396].
+
+==== 3.4.2
+
+* link:#updateOptions[`INSERT/UPDATE options`] for tables having a
+default_time_to_live specifying a TTL of 0 will remove the TTL from the
+inserted or updated values
+* link:#alterTableStmt[`ALTER TABLE`] `ADD` and `DROP` now allow mutiple
+columns to be added/removed
+* New link:#selectLimit[`PER PARTITION LIMIT`] option (see
+https://issues.apache.org/jira/browse/CASSANDRA-7017)[CASSANDRA-7017].
+* link:#udfs[User-defined functions] can now instantiate `UDTValue` and
+`TupleValue` instances via the new `UDFContext` interface (see
+https://issues.apache.org/jira/browse/CASSANDRA-10818)[CASSANDRA-10818].
+* ``User-defined types''#createTypeStmt may now be stored in a
+non-frozen form, allowing individual fields to be updated and deleted in
+link:#updateStmt[`UPDATE` statements] and link:#deleteStmt[`DELETE`
+statements], respectively.
+(https://issues.apache.org/jira/browse/CASSANDRA-7423)[CASSANDRA-7423]
+
+==== 3.4.1
+
+* Adds `CAST` functions. See link:#castFun[`Cast`].
+
+==== 3.4.0
+
+* Support for link:#createMVStmt[materialized views]
+* link:#deleteStmt[`DELETE`] support for inequality expressions and `IN`
+restrictions on any primary key columns
+* link:#updateStmt[`UPDATE`] support for `IN` restrictions on any
+primary key columns
+
+==== 3.3.1
+
+* The syntax `TRUNCATE TABLE X` is now accepted as an alias for
+`TRUNCATE X`
+
+==== 3.3.0
+
+* Adds new link:#aggregates[aggregates]
+* User-defined functions are now supported through
+link:#createFunctionStmt[`CREATE FUNCTION`] and
+link:#dropFunctionStmt[`DROP FUNCTION`].
+* User-defined aggregates are now supported through
+link:#createAggregateStmt[`CREATE AGGREGATE`] and
+link:#dropAggregateStmt[`DROP AGGREGATE`].
+* Allows double-dollar enclosed strings literals as an alternative to
+single-quote enclosed strings.
+* Introduces Roles to supercede user based authentication and access
+control
+* link:#usingdates[`Date`] and link:usingtime[`Time`] data types have
+been added
+* link:#json[`JSON`] support has been added
+* `Tinyint` and `Smallint` data types have been added
+* Adds new time conversion functions and deprecate `dateOf` and
+`unixTimestampOf`. See link:#timeFun[`Time conversion functions`]
+
+==== 3.2.0
+
+* User-defined types are now supported through
+link:#createTypeStmt[`CREATE TYPE`], link:#alterTypeStmt[`ALTER TYPE`],
+and link:#dropTypeStmt[`DROP TYPE`]
+* link:#createIndexStmt[`CREATE INDEX`] now supports indexing collection
+columns, including indexing the keys of map collections through the
+`keys()` function
+* Indexes on collections may be queried using the new `CONTAINS` and
+`CONTAINS KEY` operators
+* Tuple types were added to hold fixed-length sets of typed positional
+fields (see the section on link:#types[types] )
+* link:#dropIndexStmt[`DROP INDEX`] now supports optionally specifying a
+keyspace
+
+==== 3.1.7
+
+* `SELECT` statements now support selecting multiple rows in a single
+partition using an `IN` clause on combinations of clustering columns.
+See link:#selectWhere[SELECT WHERE] clauses.
+* `IF NOT EXISTS` and `IF EXISTS` syntax is now supported by
+`CREATE USER` and `DROP USER` statmenets, respectively.
+
+==== 3.1.6
+
+* A new link:#uuidFun[`uuid` method] has been added.
+* Support for `DELETE ... IF EXISTS` syntax.
+
+==== 3.1.5
+
+* It is now possible to group clustering columns in a relatiion, see
+link:#selectWhere[SELECT WHERE] clauses.
+* Added support for `STATIC` columns, see link:#createTableStatic[static
+in CREATE TABLE].
+
+==== 3.1.4
+
+* `CREATE INDEX` now allows specifying options when creating CUSTOM
+indexes (see link:#createIndexStmt[CREATE INDEX reference] ).
+
+==== 3.1.3
+
+* Millisecond precision formats have been added to the timestamp parser
+(see link:#usingtimestamps[working with dates] ).
+
+==== 3.1.2
+
+* `NaN` and `Infinity` has been added as valid float contants. They are
+now reserved keywords. In the unlikely case you we using them as a
+column identifier (or keyspace/table one), you will noew need to double
+quote them (see link:#identifiers[quote identifiers] ).
+
+==== 3.1.1
+
+* `SELECT` statement now allows listing the partition keys (using the
+`DISTINCT` modifier). See
+https://issues.apache.org/jira/browse/CASSANDRA-4536[CASSANDRA-4536].
+* The syntax `c IN ?` is now supported in `WHERE` clauses. In that case,
+the value expected for the bind variable will be a list of whatever type
+`c` is.
+* It is now possible to use named bind variables (using `:name` instead
+of `?`).
+
+==== 3.1.0
+
+* link:#alterTableStmt[ALTER TABLE] `DROP` option has been reenabled for
+CQL3 tables and has new semantics now: the space formerly used by
+dropped columns will now be eventually reclaimed (post-compaction). You
+should not readd previously dropped columns unless you use timestamps
+with microsecond precision (see
+https://issues.apache.org/jira/browse/CASSANDRA-3919[CASSANDRA-3919] for
+more details).
+* `SELECT` statement now supports aliases in select clause. Aliases in
+WHERE and ORDER BY clauses are not supported. See the
+link:#selectStmt[section on select] for details.
+* `CREATE` statements for `KEYSPACE`, `TABLE` and `INDEX` now supports
+an `IF NOT EXISTS` condition. Similarly, `DROP` statements support a
+`IF EXISTS` condition.
+* `INSERT` statements optionally supports a `IF NOT EXISTS` condition
+and `UPDATE` supports `IF` conditions.
+
+==== 3.0.5
+
+* `SELECT`, `UPDATE`, and `DELETE` statements now allow empty `IN`
+relations (see
+https://issues.apache.org/jira/browse/CASSANDRA-5626)[CASSANDRA-5626].
+
+==== 3.0.4
+
+* Updated the syntax for custom link:#createIndexStmt[secondary
+indexes].
+* Non-equal condition on the partition key are now never supported, even
+for ordering partitioner as this was not correct (the order was *not*
+the one of the type of the partition key). Instead, the `token` method
+should always be used for range queries on the partition key (see
+link:#selectWhere[WHERE clauses] ).
+
+==== 3.0.3
+
+* Support for custom link:#createIndexStmt[secondary indexes] has been
+added.
+
+==== 3.0.2
+
+* Type validation for the link:#constants[constants] has been fixed. For
+instance, the implementation used to allow `'2'` as a valid value for an
+`int` column (interpreting it has the equivalent of `2`), or `42` as a
+valid `blob` value (in which case `42` was interpreted as an hexadecimal
+representation of the blob). This is no longer the case, type validation
+of constants is now more strict. See the link:#types[data types] section
+for details on which constant is allowed for which type.
+* The type validation fixed of the previous point has lead to the
+introduction of link:#constants[blobs constants] to allow inputing
+blobs. Do note that while inputing blobs as strings constant is still
+supported by this version (to allow smoother transition to blob
+constant), it is now deprecated (in particular the link:#types[data
+types] section does not list strings constants as valid blobs) and will
+be removed by a future version. If you were using strings as blobs, you
+should thus update your client code ASAP to switch blob constants.
+* A number of functions to convert native types to blobs have also been
+introduced. Furthermore the token function is now also allowed in select
+clauses. See the link:#functions[section on functions] for details.
+
+==== 3.0.1
+
+* link:#usingtimestamps[Date strings] (and timestamps) are no longer
+accepted as valid `timeuuid` values. Doing so was a bug in the sense
+that date string are not valid `timeuuid`, and it was thus resulting in
+https://issues.apache.org/jira/browse/CASSANDRA-4936[confusing
+behaviors]. However, the following new methods have been added to help
+working with `timeuuid`: `now`, `minTimeuuid`, `maxTimeuuid` , `dateOf`
+and `unixTimestampOf`. See the link:#timeuuidFun[section dedicated to
+these methods] for more detail.
+* ``Float constants''#constants now support the exponent notation. In
+other words, `4.2E10` is now a valid floating point value.
+
+=== Versioning
+
+Versioning of the CQL language adheres to the http://semver.org[Semantic
+Versioning] guidelines. Versions take the form X.Y.Z where X, Y, and Z
+are integer values representing major, minor, and patch level
+respectively. There is no correlation between Cassandra release versions
+and the CQL language version.
+
+[cols=",",options="header",]
+|===
+|version |description
+|Major |The major version _must_ be bumped when backward incompatible
+changes are introduced. This should rarely occur.
+
+|Minor |Minor version increments occur when new, but backward
+compatible, functionality is introduced.
+
+|Patch |The patch version is incremented when bugs are fixed.
+|===
diff --cc doc/modules/cassandra/pages/cql/dml.adoc
index 8a4df2fecb,0000000000..d0517aaf34
mode 100644,000000..100644
--- a/doc/modules/cassandra/pages/cql/dml.adoc
+++ b/doc/modules/cassandra/pages/cql/dml.adoc
@@@ -1,458 -1,0 +1,461 @@@
+= Data Manipulation
+
+This section describes the statements supported by CQL to insert,
+update, delete and query data.
+
+[[select-statement]]
+== SELECT
+
+Querying data from data is done using a `SELECT` statement:
+
+[source,bnf]
+----
+include::example$BNF/select_statement.bnf[]
+----
+
+For example:
+
+[source,cql]
+----
+include::example$CQL/select_statement.cql[]
+----
+
+The `SELECT` statements reads one or more columns for one or more rows
+in a table. It returns a result-set of the rows matching the request,
+where each row contains the values for the selection corresponding to
+the query. Additionally, xref:cql/functions.adoc#cql-functions[functions] including
+xref:cql/functions.adoc#aggregate-functions[aggregations] can be applied to the result.
+
+A `SELECT` statement contains at least a xref:cql/dml.adoc#selection-clause[selection clause] and the name of the table on which
+the selection is executed.
+CQL does *not* execute joins or sub-queries and a select statement only apply to a single table.
+A select statement can also have a xref:cql/dml.adoc#where-clause[where clause] that can further narrow the query results.
+Additional clauses can xref:cql/dml.adoc#ordering-clause[order] or xref:cql/dml.adoc#limit-clause[limit] the results.
+Lastly, xref:cql/dml.adoc#allow-filtering[queries that require full cluster filtering] can append `ALLOW FILTERING` to any query.
+
+[[selection-clause]]
+=== Selection clause
+
+The `select_clause` determines which columns will be queried and returned in the result set.
+This clause can also apply transformations to apply to the result before returning.
+The selection clause consists of a comma-separated list of specific _selectors_ or, alternatively, the wildcard character (`*`) to select all the columns defined in the table.
+
+==== Selectors
+
+A `selector` can be one of:
+
+* A column name of the table selected, to retrieve the values for that
+column.
+* A term, which is usually used nested inside other selectors like
+functions (if a term is selected directly, then the corresponding column
+of the result-set will simply have the value of this term for every row
+returned).
+* A casting, which allows to convert a nested selector to a (compatible)
+type.
+* A function call, where the arguments are selector themselves. See the
+section on xref:cql/functions.adoc#cql-functions[functions] for more details.
+* The special call `COUNT(*)` to the xref:cql/functions.adoc#count-function[COUNT function],
+which counts all non-null results.
+
+==== Aliases
+
+Every _top-level_ selector can also be aliased (using AS).
+If so, the name of the corresponding column in the result set will be
+that of the alias. For instance:
+
+[source,cql]
+----
+include::example$CQL/as.cql[]
+----
+
+[NOTE]
+====
+Currently, aliases aren't recognized in the `WHERE` or `ORDER BY` clauses in the statement.
+You must use the orignal column name instead.
+====
+
+[[writetime-and-ttl-function]]
+==== `WRITETIME` and `TTL` function
+
+Selection supports two special functions that aren't allowed anywhere
+else: `WRITETIME` and `TTL`.
+Both functions take only one argument, a column name.
+These functions retrieve meta-information that is stored internally for each column:
+
+* `WRITETIME` stores the timestamp of the value of the column
+* `TTL` stores the remaining time to live (in seconds) for the value of the column if it is set to expire; otherwise the value is `null`.
+
++The `WRITETIME` and `TTL` functions can't be used on multi-cell columns such as non-frozen
++collections or non-frozen user-defined types.
++
+[[where-clause]]
+=== The `WHERE` clause
+
+The `WHERE` clause specifies which rows are queried. It specifies
+a relationship for `PRIMARY KEY` columns or a column that has
+a xref:cql/indexes.adoc#create-index-statement[secondary index] defined, along with a set value.
+
+Not all relationships are allowed in a query. For instance, only an equality
+is allowed on a partition key. The `IN` clause is considered an equality for one or more values.
+The `TOKEN` clause can be used to query for partition key non-equalities.
+A partition key must be specified before clustering columns in the `WHERE` clause. The relationship
+for clustering columns must specify a *contiguous* set of rows to order.
+
+For instance, given:
+
+[source,cql]
+----
+include::example$CQL/table_for_where.cql[]
+----
+
+The following query is allowed:
+
+[source,cql]
+----
+include::example$CQL/where.cql[]
+----
+
+But the following one is not, as it does not select a contiguous set of
+rows (and we suppose no secondary indexes are set):
+
+[source,cql]
+----
+include::example$CQL/where_fail.cql[]
+----
+
+When specifying relationships, the `TOKEN` function can be applied to the `PARTITION KEY` column to query.
+Rows will be selected based on the token of the `PARTITION_KEY` rather than on the value.
+[IMPORTANT]
+====
+The token of a key depends on the partitioner in use, and that
+in particular the `RandomPartitioner` won't yield a meaningful order.
+Also note that ordering partitioners always order token values by bytes (so
+even if the partition key is of type int, `token(-1) > token(0)` in
+particular).
+====
+
+For example:
+
+[source,cql]
+----
+include::example$CQL/token.cql[]
+----
+
+The `IN` relationship is only allowed on the last column of the
+partition key or on the last column of the full primary key.
+
+It is also possible to “group” `CLUSTERING COLUMNS` together in a
+relation using the tuple notation.
+
+For example:
+
+[source,cql]
+----
+include::example$CQL/where_group_cluster_columns.cql[]
+----
+
+This query will return all rows that sort after the one having “John's Blog” as
+`blog_tile` and '2012-01-01' for `posted_at` in the clustering order. In
+particular, rows having a `post_at <= '2012-01-01'` will be returned, as
+long as their `blog_title > 'John''s Blog'`.
+
+That would not be the case for this example:
+
+[source,cql]
+----
+include::example$CQL/where_no_group_cluster_columns.cql[]
+----
+
+The tuple notation may also be used for `IN` clauses on clustering columns:
+
+[source,cql]
+----
+include::example$CQL/where_in_tuple.cql[]
+----
+
+The `CONTAINS` operator may only be used for collection columns (lists,
+sets, and maps). In the case of maps, `CONTAINS` applies to the map
+values. The `CONTAINS KEY` operator may only be used on map columns and
+applies to the map keys.
+
+[[group-by-clause]]
+=== Grouping results
+
+The `GROUP BY` option can condense all selected
+rows that share the same values for a set of columns into a single row.
+
+Using the `GROUP BY` option, rows can be grouped at the partition key or clustering column level.
+Consequently, the `GROUP BY` option only accepts primary key columns in defined order as arguments.
+If a primary key column is restricted by an equality restriction, it is not included in the `GROUP BY` clause.
+
+Aggregate functions will produce a separate value for each group.
+If no `GROUP BY` clause is specified, aggregates functions will produce a single value for all the rows.
+
+If a column is selected without an aggregate function, in a statement
+with a `GROUP BY`, the first value encounter in each group will be
+returned.
+
+[[ordering-clause]]
+=== Ordering results
+
+The `ORDER BY` clause selects the order of the returned results.
+The argument is a list of column names and each column's order
+(`ASC` for ascendant and `DESC` for descendant,
+The possible orderings are limited by the xref:cql/ddl.adoc#clustering-order[clustering order] defined on the table:
+
+* if the table has been defined without any specific `CLUSTERING ORDER`, then the order is as defined by the clustering columns
+or the reverse
+* otherwise, the order is defined by the `CLUSTERING ORDER` option and the reversed one.
+
+[[limit-clause]]
+=== Limiting results
+
+The `LIMIT` option to a `SELECT` statement limits the number of rows
+returned by a query. The `PER PARTITION LIMIT` option limits the
+number of rows returned for a given partition by the query. Both types of limits can used in the same statement.
+
+[[allow-filtering]]
+=== Allowing filtering
+
+By default, CQL only allows select queries that don't involve a full scan of all partitions.
+If all partitions are scanned, then returning the results may experience a significant latency proportional to the
+amount of data in the table. The `ALLOW FILTERING` option explicitly executes a full scan. Thus, the performance of
+the query can be unpredictable.
+
+For example, consider the following table of user profiles with birth year and country of residence.
+The birth year has a secondary index defined.
+
+[source,cql]
+----
+include::example$CQL/allow_filtering.cql[]
+----
+
+The following queries are valid:
+
+[source,cql]
+----
+include::example$CQL/query_allow_filtering.cql[]
+----
+
+In both cases, the query performance is proportional to the amount of data returned.
+The first query returns all rows, because all users are selected.
+The second query returns only the rows defined by the secondary index, a per-node implementation; the results will
+depend on the number of nodes in the cluster, and is indirectly proportional to the amount of data stored.
+The number of nodes will always be multiple number of magnitude lower than the number of user profiles stored.
+Both queries may return very large result sets, but the addition of a `LIMIT` clause can reduced the latency.
+
+The following query will be rejected:
+
+[source,cql]
+----
+include::example$CQL/query_fail_allow_filtering.cql[]
+----
+
+Cassandra cannot guarantee that large amounts of data won't have to scanned amount of data, even if the result is small.
+If you know that the dataset is small, and the performance will be reasonable, add `ALLOW FILTERING` to allow the query to
+execute:
+
+[source,cql]
+----
+include::example$CQL/query_nofail_allow_filtering.cql[]
+----
+
+[[insert-statement]]
+== INSERT
+
+Inserting data for a row is done using an `INSERT` statement:
+
+[source,bnf]
+----
+include::example$BNF/insert_statement.bnf[]
+----
+
+For example:
+
+[source,cql]
+----
+include::example$CQL/insert_statement.cql[]
+----
+
+The `INSERT` statement writes one or more columns for a given row in a
+table.
+Since a row is identified by its `PRIMARY KEY`, at least one columns must be specified.
+The list of columns to insert must be supplied with the `VALUES` syntax.
+When using the `JSON` syntax, `VALUES` are optional.
+See the section on xref:cql/dml.adoc#cql-json[JSON support] for more detail.
+All updates for an `INSERT` are applied atomically and in isolation.
+
+Unlike in SQL, `INSERT` does not check the prior existence of the row by default.
+The row is created if none existed before, and updated otherwise.
+Furthermore, there is no means of knowing which action occurred.
+
+The `IF NOT EXISTS` condition can restrict the insertion if the row does not exist.
+However, note that using `IF NOT EXISTS` will incur a non-negligible performance cost, because Paxos is used,
+so this should be used sparingly.
+
+Please refer to the xref:cql/dml.adoc#update-parameters[UPDATE] section for informations on the `update_parameter`.
+Also note that `INSERT` does not support counters, while `UPDATE` does.
+
+[[update-statement]]
+== UPDATE
+
+Updating a row is done using an `UPDATE` statement:
+
+[source, bnf]
+----
+include::example$BNF/update_statement.bnf[]
+----
+
+For instance:
+
+[source,cql]
+----
+include::example$CQL/update_statement.cql[]
+----
+
+The `UPDATE` statement writes one or more columns for a given row in a
+table.
+The `WHERE`clause is used to select the row to update and must include all columns of the `PRIMARY KEY`.
+Non-primary key columns are set using the `SET` keyword.
+In an `UPDATE` statement, all updates within the same partition key are applied atomically and in isolation.
+
+Unlike in SQL, `UPDATE` does not check the prior existence of the row by default.
+The row is created if none existed before, and updated otherwise.
+Furthermore, there is no means of knowing which action occurred.
+
+The `IF` condition can be used to choose whether the row is updated or not if a particular condition is met.
+However, like the `IF NOT EXISTS` condition, a non-negligible performance cost can be incurred.
+
+Regarding the `SET` assignment:
+
+* `c = c + 3` will increment/decrement counters, the only operation allowed.
+The column name after the '=' sign *must* be the same than the one before the '=' sign.
+Increment/decrement is only allowed on counters.
+See the section on xref:cql/dml.adoc#counters[counters] for details.
+* `id = id + <some-collection>` and `id[value1] = value2` are for collections.
+See the xref:cql/types.adoc#collections[collections] for details.
+* `id.field = 3` is for setting the value of a field on a non-frozen user-defined types.
+See the xref:cql/types.adoc#udts[UDTs] for details.
+
+=== Update parameters
+
+`UPDATE` and `INSERT` statements support the following parameters:
+
+* `TTL`: specifies an optional Time To Live (in seconds) for the
+inserted values. If set, the inserted values are automatically removed
+from the database after the specified time. Note that the TTL concerns
+the inserted values, not the columns themselves. This means that any
+subsequent update of the column will also reset the TTL (to whatever TTL
+is specified in that update). By default, values never expire. A TTL of
+0 is equivalent to no TTL. If the table has a default_time_to_live, a
+TTL of 0 will remove the TTL for the inserted or updated values. A TTL
+of `null` is equivalent to inserting with a TTL of 0.
+
+`UPDATE`, `INSERT`, `DELETE` and `BATCH` statements support the following parameters:
+
+* `TIMESTAMP`: sets the timestamp for the operation. If not specified,
+the coordinator will use the current time (in microseconds) at the start
+of statement execution as the timestamp. This is usually a suitable
+default.
+
+[[delete_statement]]
+== DELETE
+
+Deleting rows or parts of rows uses the `DELETE` statement:
+
+[source,bnf]
+----
+include::example$BNF/delete_statement.bnf[]
+----
+
+For example:
+
+[source,cql]
+----
+include::example$CQL/delete_statement.cql[]
+----
+
+The `DELETE` statement deletes columns and rows. If column names are
+provided directly after the `DELETE` keyword, only those columns are
+deleted from the row indicated by the `WHERE` clause. Otherwise, whole
+rows are removed.
+
+The `WHERE` clause specifies which rows are to be deleted. Multiple rows
+may be deleted with one statement by using an `IN` operator. A range of
+rows may be deleted using an inequality operator (such as `>=`).
+
+`DELETE` supports the `TIMESTAMP` option with the same semantics as in
+xref:cql/dml.adoc#update-parameters[updates].
+
+In a `DELETE` statement, all deletions within the same partition key are
+applied atomically and in isolation.
+
+A `DELETE` operation can be conditional through the use of an `IF`
+clause, similar to `UPDATE` and `INSERT` statements. However, as with
+`INSERT` and `UPDATE` statements, this will incur a non-negligible
+performance cost because Paxos is used, and should be used sparingly.
+
+[[batch_statement]]
+== BATCH
+
+Multiple `INSERT`, `UPDATE` and `DELETE` can be executed in a single
+statement by grouping them through a `BATCH` statement:
+
+[source, bnf]
+----
+include::example$BNF/batch_statement.bnf[]
+----
+
+For instance:
+
+[source,cql]
+----
+include::example$CQL/batch_statement.cql[]
+----
+
+The `BATCH` statement group multiple modification statements
+(insertions/updates and deletions) into a single statement. It serves
+several purposes:
+
+* It saves network round-trips between the client and the server (and
+sometimes between the server coordinator and the replicas) when batching
+multiple updates.
+* All updates in a `BATCH` belonging to a given partition key are
+performed in isolation.
+* By default, all operations in the batch are performed as _logged_, to
+ensure all mutations eventually complete (or none will). See the notes
+on xref:cql/dml.adoc#unlogged-batches[UNLOGGED batches] for more details.
+
+Note that:
+
+* `BATCH` statements may only contain `UPDATE`, `INSERT` and `DELETE`
+statements (not other batches for instance).
+* Batches are _not_ a full analogue for SQL transactions.
+* If a timestamp is not specified for each operation, then all
+operations will be applied with the same timestamp (either one generated
+automatically, or the timestamp provided at the batch level). Due to
+Cassandra's conflict resolution procedure in the case of
+http://wiki.apache.org/cassandra/FAQ#clocktie[timestamp ties],
+operations may be applied in an order that is different from the order
+they are listed in the `BATCH` statement. To force a particular
+operation ordering, you must specify per-operation timestamps.
+* A LOGGED batch to a single partition will be converted to an UNLOGGED
+batch as an optimization.
+
+[[unlogged-batches]]
+=== `UNLOGGED` batches
+
+By default, Cassandra uses a batch log to ensure all operations in a
+batch eventually complete or none will (note however that operations are
+only isolated within a single partition).
+
+There is a performance penalty for batch atomicity when a batch spans
+multiple partitions. If you do not want to incur this penalty, you can
+tell Cassandra to skip the batchlog with the `UNLOGGED` option. If the
+`UNLOGGED` option is used, a failed batch might leave the patch only
+partly applied.
+
+=== `COUNTER` batches
+
+Use the `COUNTER` option for batched counter updates. Unlike other
+updates in Cassandra, counter updates are not idempotent.
diff --cc src/java/org/apache/cassandra/cql3/selection/Selectable.java
index 80e2ae8778,6297f6431e..5cb9b6c6b6
--- a/src/java/org/apache/cassandra/cql3/selection/Selectable.java
+++ b/src/java/org/apache/cassandra/cql3/selection/Selectable.java
@@@ -199,25 -84,21 +199,27 @@@ public interface Selectable extends Ass
throw new InvalidRequestException(
String.format("Cannot use selection function %s on PRIMARY KEY part %s",
isWritetime ? "writeTime" : "ttl",
- def.name));
- if (def.type.isMultiCell())
- throw new InvalidRequestException(String.format("Cannot use selection function %s on non-frozen collection %s",
+ column.name));
- if (column.type.isCollection())
- throw new InvalidRequestException(String.format("Cannot use selection function %s on collections",
- isWritetime ? "writeTime" : "ttl"));
++ if (column.type.isMultiCell())
++ throw new InvalidRequestException(String.format("Cannot use selection function %s on non-frozen %s %s",
+ isWritetime ? "writeTime" : "ttl",
- def.name));
++ column.type.isCollection() ? "collection" : "UDT",
++ column.name));
- return WritetimeOrTTLSelector.newFactory(def, addAndGetIndex(def, defs), isWritetime);
+ return WritetimeOrTTLSelector.newFactory(column, addAndGetIndex(column, defs), isWritetime);
}
- public static class Raw implements Selectable.Raw
+ public AbstractType<?> getExactTypeIfKnown(String keyspace)
{
- private final ColumnIdentifier.Raw id;
+ return isWritetime ? LongType.instance : Int32Type.instance;
+ }
+
+ public static class Raw extends Selectable.Raw
+ {
+ private final ColumnDefinition.Raw id;
private final boolean isWritetime;
- public Raw(ColumnIdentifier.Raw id, boolean isWritetime)
+ public Raw(ColumnDefinition.Raw id, boolean isWritetime)
{
this.id = id;
this.isWritetime = isWritetime;
diff --cc test/unit/org/apache/cassandra/cql3/validation/entities/WritetimeOrTTLTest.java
index 0000000000,24ff8bc272..cc6c663696
mode 000000,100644..100644
--- a/test/unit/org/apache/cassandra/cql3/validation/entities/WritetimeOrTTLTest.java
+++ b/test/unit/org/apache/cassandra/cql3/validation/entities/WritetimeOrTTLTest.java
@@@ -1,0 -1,255 +1,264 @@@
+ /*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+ package org.apache.cassandra.cql3.validation.entities;
+
+ import org.junit.Test;
+
+ import org.apache.cassandra.cql3.CQLTester;
+ import org.apache.cassandra.cql3.UntypedResultSet;
+ import org.apache.cassandra.exceptions.InvalidRequestException;
+
+ import static org.junit.Assert.assertNotNull;
+ import static org.junit.Assert.assertNull;
+ import static org.junit.Assert.assertTrue;
+ import static java.lang.String.format;
+
+ public class WritetimeOrTTLTest extends CQLTester
+ {
+ private static final long TIMESTAMP_1 = 1;
+ private static final long TIMESTAMP_2 = 2;
+ private static final Long NO_TIMESTAMP = null;
+
+ private static final int TTL_1 = 10000;
+ private static final int TTL_2 = 20000;
+ private static final Integer NO_TTL = null;
+
+ @Test
+ public void testSimple() throws Throwable
+ {
+ createTable("CREATE TABLE %s (pk int, ck int, v int, PRIMARY KEY(pk, ck))");
+
+ // Primary key columns should be rejected
+ assertInvalidPrimaryKeySelection("pk");
+ assertInvalidPrimaryKeySelection("ck");
+
+ // No rows
+ assertEmpty(execute("SELECT WRITETIME(v) FROM %s"));
+ assertEmpty(execute("SELECT TTL(v) FROM %s"));
+
+ // Insert row without TTL
+ execute("INSERT INTO %s (pk, ck, v) VALUES (1, 2, 3) USING TIMESTAMP ?", TIMESTAMP_1);
+ assertWritetimeAndTTL("v", TIMESTAMP_1, NO_TTL);
+
+ // Update the row with TTL and a new timestamp
+ execute("UPDATE %s USING TIMESTAMP ? AND TTL ? SET v=8 WHERE pk=1 AND ck=2", TIMESTAMP_2, TTL_1);
+ assertWritetimeAndTTL("v", TIMESTAMP_2, TTL_1);
+
+ // Combine with other columns
+ assertRows("SELECT pk, WRITETIME(v) FROM %s", row(1, TIMESTAMP_2));
+ assertRows("SELECT WRITETIME(v), pk FROM %s", row(TIMESTAMP_2, 1));
+ assertRows("SELECT pk, WRITETIME(v), v, ck FROM %s", row(1, TIMESTAMP_2, 8, 2));
+ }
+
+ @Test
+ public void testList() throws Throwable
+ {
+ createTable("CREATE TABLE %s (k int PRIMARY KEY, l list<int>)");
- assertInvalidMultiCellSelection("l");
++ assertInvalidMultiCellSelection("l", true);
+ }
+
+ @Test
+ public void testFrozenList() throws Throwable
+ {
+ createTable("CREATE TABLE %s (k int PRIMARY KEY, v frozen<list<int>>)");
+
+ // Null column
+ execute("INSERT INTO %s (k) VALUES (1) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("v", NO_TIMESTAMP, NO_TTL);
+
+ // Create empty
+ execute("INSERT INTO %s (k, v) VALUES (1, []) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("v", TIMESTAMP_1, TTL_1);
+
+ // Update with a single element without TTL
+ execute("INSERT INTO %s (k, v) VALUES (1, [1]) USING TIMESTAMP ?", TIMESTAMP_1);
+ assertWritetimeAndTTL("v", TIMESTAMP_1, NO_TTL);
+
+ // Add a new element to the list with a new timestamp and a TTL
+ execute("INSERT INTO %s (k, v) VALUES (1, [1, 2, 3]) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_2, TTL_2);
+ assertWritetimeAndTTL("v", TIMESTAMP_2, TTL_2);
+ }
+
+ @Test
+ public void testSet() throws Throwable
+ {
+ createTable("CREATE TABLE %s (k int PRIMARY KEY, s set<int>)");
- assertInvalidMultiCellSelection("s");
++ assertInvalidMultiCellSelection("s", true);
+ }
+
+ @Test
+ public void testFrozenSet() throws Throwable
+ {
+ createTable("CREATE TABLE %s (k int PRIMARY KEY, s frozen<set<int>>)");
+
+ // Null column
+ execute("INSERT INTO %s (k) VALUES (1) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("s", NO_TIMESTAMP, NO_TTL);
+
+ // Create empty
+ execute("INSERT INTO %s (k, s) VALUES (1, {}) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("s", TIMESTAMP_1, TTL_1);
+
+ // Update with a single element without TTL
+ execute("INSERT INTO %s (k, s) VALUES (1, {1}) USING TIMESTAMP ?", TIMESTAMP_1);
+ assertWritetimeAndTTL("s", TIMESTAMP_1, NO_TTL);
+
+ // Add a new element to the set with a new timestamp and a TTL
+ execute("INSERT INTO %s (k, s) VALUES (1, {1, 2}) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_2, TTL_2);
+ assertWritetimeAndTTL("s", TIMESTAMP_2, TTL_2);
+ }
+
+ @Test
+ public void testMap() throws Throwable
+ {
+ createTable("CREATE TABLE %s (k int PRIMARY KEY, m map<int, int>)");
- assertInvalidMultiCellSelection("m");
++ assertInvalidMultiCellSelection("m", true);
+ }
+
+ @Test
+ public void testFrozenMap() throws Throwable
+ {
+ createTable("CREATE TABLE %s (k int PRIMARY KEY, m frozen<map<int,int>>)");
+
+ // Null column
+ execute("INSERT INTO %s (k) VALUES (1) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("m", NO_TIMESTAMP, NO_TTL);
+
+ // Create empty
+ execute("INSERT INTO %s (k, m) VALUES (1, {}) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("m", TIMESTAMP_1, TTL_1);
+
+ // Create with a single element without TTL
+ execute("INSERT INTO %s (k, m) VALUES (1, {1:10}) USING TIMESTAMP ?", TIMESTAMP_1);
+ assertWritetimeAndTTL("m", TIMESTAMP_1, NO_TTL);
+
+ // Add a new element to the map with a new timestamp and a TTL
+ execute("INSERT INTO %s (k, m) VALUES (1, {1:10, 2:20}) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_2, TTL_2);
+ assertWritetimeAndTTL("m", TIMESTAMP_2, TTL_2);
+ }
+
++ @Test
++ public void testUDT() throws Throwable
++ {
++ String type = createType("CREATE TYPE %s (f1 int, f2 int)");
++ createTable("CREATE TABLE %s (k int PRIMARY KEY, t " + type + ')');
++ assertInvalidMultiCellSelection("t", false);
++ }
++
+ @Test
+ public void testFrozenUDT() throws Throwable
+ {
+ String type = createType("CREATE TYPE %s (f1 int, f2 int)");
+ createTable("CREATE TABLE %s (k int PRIMARY KEY, t frozen<" + type + ">)");
+
+ // Null column
+ execute("INSERT INTO %s (k) VALUES (0) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("t", NO_TIMESTAMP, NO_TTL);
+
+ // Both fields are empty
+ execute("INSERT INTO %s (k, t) VALUES (0, {f1:null, f2:null}) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("t", "k=0", TIMESTAMP_1, TTL_1);
+
+ // Only the first field is set
+ execute("INSERT INTO %s (k, t) VALUES (1, {f1:1, f2:null}) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("t", "k=1", TIMESTAMP_1, TTL_1);
+
+ // Only the second field is set
+ execute("INSERT INTO %s (k, t) VALUES (2, {f1:null, f2:2}) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("t", "k=2", TIMESTAMP_1, TTL_1);
+
+ // Both fields are set
+ execute("INSERT INTO %s (k, t) VALUES (3, {f1:1, f2:2}) USING TIMESTAMP ? AND TTL ?", TIMESTAMP_1, TTL_1);
+ assertWritetimeAndTTL("t", "k=3", TIMESTAMP_1, TTL_1);
+ }
+
+ private void assertRows(String query, Object[]... rows) throws Throwable
+ {
+ assertRows(execute(query), rows);
+ }
+
+ private void assertWritetimeAndTTL(String column, Long timestamp, Integer ttl) throws Throwable
+ {
+ assertWritetimeAndTTL(column, null, timestamp, ttl);
+ }
+
+ private void assertWritetimeAndTTL(String column, String where, Long timestamp, Integer ttl)
+ throws Throwable
+ {
+ where = where == null ? "" : " WHERE " + where;
+
+ // Verify write time
+ String writetimeQuery = String.format("SELECT WRITETIME(%s) FROM %%s %s", column, where);
+ assertRows(writetimeQuery, row(timestamp));
+
+ // Verify ttl
+ UntypedResultSet rs = execute(String.format("SELECT TTL(%s) FROM %%s %s", column, where));
+ assertRowCount(rs, 1);
+ UntypedResultSet.Row row = rs.one();
+ String ttlColumn = String.format("ttl(%s)", column);
+ if (ttl == null)
+ {
+ assertTTL(ttl, null);
+ }
+ else
+ {
+ assertTTL(ttl, row.getInt(ttlColumn));
+ }
+ }
+
+ /**
+ * Since the returned TTL is the remaining seconds since last update, it could be lower than the
+ * specified TTL depending on the test execution time, se we allow up to one-minute difference
+ */
+ private void assertTTL(Integer expected, Integer actual)
+ {
+ if (expected == null)
+ {
+ assertNull(actual);
+ }
+ else
+ {
+ assertNotNull(actual);
+ assertTrue(actual > expected - 60);
+ assertTrue(actual <= expected);
+ }
+ }
+
+ private void assertInvalidPrimaryKeySelection(String column) throws Throwable
+ {
+ assertInvalidThrowMessage("Cannot use selection function writeTime on PRIMARY KEY part " + column,
+ InvalidRequestException.class,
+ String.format("SELECT WRITETIME(%s) FROM %%s", column));
+ assertInvalidThrowMessage("Cannot use selection function ttl on PRIMARY KEY part " + column,
+ InvalidRequestException.class,
+ String.format("SELECT TTL(%s) FROM %%s", column));
+ }
+
- private void assertInvalidMultiCellSelection(String column) throws Throwable
++ private void assertInvalidMultiCellSelection(String column, boolean isCollection) throws Throwable
+ {
- String message = "Cannot use selection function %s on non-frozen collection " + column;
++ String message = format("Cannot use selection function %%s on non-frozen %s %s",
++ isCollection ? "collection" : "UDT", column);
+ assertInvalidThrowMessage(format(message, "writeTime"),
+ InvalidRequestException.class,
+ String.format("SELECT WRITETIME(%s) FROM %%s", column));
+ assertInvalidThrowMessage(format(message, "ttl"),
+ InvalidRequestException.class,
+ String.format("SELECT TTL(%s) FROM %%s", column));
+ }
+ }
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