= 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.