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# The Influx Query Language Specification
## Introduction
This is a reference for the Influx Query Language ("InfluxQL").
InfluxQL is a SQL-like query language for interacting with InfluxDB. It has
been lovingly crafted to feel familiar to those coming from other SQL or
SQL-like environments while providing features specific to storing and analyzing
time series data.
## Notation
The syntax is specified using Extended Backus-Naur Form ("EBNF"). EBNF is the
same notation used in the [Go](http://golang.org) programming language
specification, which can be found [here](https://golang.org/ref/spec). Not so
coincidentally, InfluxDB is written in Go.
```
Production = production_name "=" [ Expression ] "." .
Expression = Alternative { "|" Alternative } .
Alternative = Term { Term } .
Term = production_name | token [ "…" token ] | Group | Option | Repetition .
Group = "(" Expression ")" .
Option = "[" Expression "]" .
Repetition = "{" Expression "}" .
```
Notation operators in order of increasing precedence:
```
| alternation
() grouping
[] option (0 or 1 times)
{} repetition (0 to n times)
```
## Query representation
### Characters
InfluxQL is Unicode text encoded in [UTF-8](http://en.wikipedia.org/wiki/UTF-8).
```
newline = /* the Unicode code point U+000A */ .
unicode_char = /* an arbitrary Unicode code point except newline */ .
```
## Letters and digits
Letters are the set of ASCII characters plus the underscore character _ (U+005F)
is considered a letter.
Only decimal digits are supported.
```
letter = ascii_letter | "_" .
ascii_letter = "A" … "Z" | "a" … "z" .
digit = "0" … "9" .
```
## Identifiers
Identifiers are tokens which refer to database names, retention policy names,
user names, measurement names, tag keys, and field keys.
The rules:
- double quoted identifiers can contain any unicode character other than a new line
- double quoted identifiers can contain escaped `"` characters (i.e., `\"`)
- unquoted identifiers must start with an upper or lowercase ASCII character or "_"
- unquoted identifiers may contain only ASCII letters, decimal digits, and "_"
```
identifier = unquoted_identifier | quoted_identifier .
unquoted_identifier = ( letter ) { letter | digit } .
quoted_identifier = `"` unicode_char { unicode_char } `"` .
```
#### Examples:
```
cpu
_cpu_stats
"1h"
"anything really"
"1_Crazy-1337.identifier>NAME👍"
```
## Keywords
```
ALL ALTER ANY AS ASC BEGIN
BY CREATE CONTINUOUS DATABASE DATABASES DEFAULT
DELETE DESC DESTINATIONS DIAGNOSTICS DISTINCT DROP
DURATION END EVERY EXISTS EXPLAIN FIELD
FOR FORCE FROM GRANT GRANTS GROUP
GROUPS IF IN INF INNER INSERT
INTO KEY KEYS LIMIT SHOW MEASUREMENT
MEASUREMENTS NOT OFFSET ON ORDER PASSWORD
POLICY POLICIES PRIVILEGES QUERIES QUERY READ
REPLICATION RESAMPLE RETENTION REVOKE SELECT SERIES
SERVER SERVERS SET SHARD SHARDS SLIMIT
SOFFSET STATS SUBSCRIPTION SUBSCRIPTIONS TAG TO
USER USERS VALUES WHERE WITH WRITE
```
## Literals
### Integers
InfluxQL supports decimal integer literals. Hexadecimal and octal literals are
not currently supported.
```
int_lit = ( "1" … "9" ) { digit } .
```
### Floats
InfluxQL supports floating-point literals. Exponents are not currently supported.
```
float_lit = int_lit "." int_lit .
```
### Strings
String literals must be surrounded by single quotes. Strings may contain `'`
characters as long as they are escaped (i.e., `\'`).
```
string_lit = `'` { unicode_char } `'` .
```
### Durations
Duration literals specify a length of time. An integer literal followed
immediately (with no spaces) by a duration unit listed below is interpreted as
a duration literal.
### Duration units
| Units | Meaning |
|--------|-----------------------------------------|
| u or µ | microseconds (1 millionth of a second) |
| ms | milliseconds (1 thousandth of a second) |
| s | second |
| m | minute |
| h | hour |
| d | day |
| w | week |
```
duration_lit = int_lit duration_unit .
duration_unit = "u" | "µ" | "s" | "h" | "d" | "w" | "ms" .
```
### Dates & Times
The date and time literal format is not specified in EBNF like the rest of this document. It is specified using Go's date / time parsing format, which is a reference date written in the format required by InfluxQL. The reference date time is:
InfluxQL reference date time: January 2nd, 2006 at 3:04:05 PM
```
time_lit = "2006-01-02 15:04:05.999999" | "2006-01-02" .
```
### Booleans
```
bool_lit = TRUE | FALSE .
```
### Regular Expressions
```
regex_lit = "/" { unicode_char } "/" .
```
## Queries
A query is composed of one or more statements separated by a semicolon.
```
query = statement { ";" statement } .
statement = alter_retention_policy_stmt |
create_continuous_query_stmt |
create_database_stmt |
create_retention_policy_stmt |
create_subscription_stmt |
create_user_stmt |
delete_stmt |
drop_continuous_query_stmt |
drop_database_stmt |
drop_measurement_stmt |
drop_retention_policy_stmt |
drop_series_stmt |
drop_subscription_stmt |
drop_user_stmt |
grant_stmt |
show_continuous_queries_stmt |
show_databases_stmt |
show_field_keys_stmt |
show_grants_stmt |
show_measurements_stmt |
show_retention_policies |
show_series_stmt |
show_shard_groups_stmt |
show_shards_stmt |
show_subscriptions_stmt|
show_tag_keys_stmt |
show_tag_values_stmt |
show_users_stmt |
revoke_stmt |
select_stmt .
```
## Statements
### ALTER RETENTION POLICY
```
alter_retention_policy_stmt = "ALTER RETENTION POLICY" policy_name on_clause
retention_policy_option
[ retention_policy_option ]
[ retention_policy_option ] .
```
#### Examples:
```sql
-- Set default retention policy for mydb to 1h.cpu.
ALTER RETENTION POLICY "1h.cpu" ON mydb DEFAULT;
-- Change duration and replication factor.
ALTER RETENTION POLICY policy1 ON somedb DURATION 1h REPLICATION 4
```
### CREATE CONTINUOUS QUERY
```
create_continuous_query_stmt = "CREATE CONTINUOUS QUERY" query_name on_clause
[ "RESAMPLE" resample_opts ]
"BEGIN" select_stmt "END" .
query_name = identifier .
resample_opts = (every_stmt for_stmt | every_stmt | for_stmt) .
every_stmt = "EVERY" duration_lit
for_stmt = "FOR" duration_lit
```
#### Examples:
```sql
-- selects from default retention policy and writes into 6_months retention policy
CREATE CONTINUOUS QUERY "10m_event_count"
ON db_name
BEGIN
SELECT count(value)
INTO "6_months".events
FROM events
GROUP BY time(10m)
END;
-- this selects from the output of one continuous query in one retention policy and outputs to another series in another retention policy
CREATE CONTINUOUS QUERY "1h_event_count"
ON db_name
BEGIN
SELECT sum(count) as count
INTO "2_years".events
FROM "6_months".events
GROUP BY time(1h)
END;
-- this customizes the resample interval so the interval is queried every 10s and intervals are resampled until 2m after their start time
-- when resample is used, at least one of "EVERY" or "FOR" must be used
CREATE CONTINUOUS QUERY "cpu_mean"
ON db_name
RESAMPLE EVERY 10s FOR 2m
BEGIN
SELECT mean(value)
INTO "cpu_mean"
FROM "cpu"
GROUP BY time(1m)
END;
```
### CREATE DATABASE
```
create_database_stmt = "CREATE DATABASE" db_name .
```
#### Example:
```sql
CREATE DATABASE foo
```
### CREATE RETENTION POLICY
```
create_retention_policy_stmt = "CREATE RETENTION POLICY" policy_name on_clause
retention_policy_duration
retention_policy_replication
[ "DEFAULT" ] .
```
#### Examples
```sql
-- Create a retention policy.
CREATE RETENTION POLICY "10m.events" ON somedb DURATION 10m REPLICATION 2;
-- Create a retention policy and set it as the default.
CREATE RETENTION POLICY "10m.events" ON somedb DURATION 10m REPLICATION 2 DEFAULT;
```
### CREATE SUBSCRIPTION
```
create_subscription_stmt = "CREATE SUBSCRIPTION" subscription_name "ON" db_name "." retention_policy "DESTINATIONS" ("ANY"|"ALL") host { "," host} .
```
#### Examples:
```sql
-- Create a SUBSCRIPTION on database 'mydb' and retention policy 'default' that send data to 'example.com:9090' via UDP.
CREATE SUBSCRIPTION sub0 ON "mydb"."default" DESTINATIONS ALL 'udp://example.com:9090' ;
-- Create a SUBSCRIPTION on database 'mydb' and retention policy 'default' that round robins the data to 'h1.example.com:9090' and 'h2.example.com:9090'.
CREATE SUBSCRIPTION sub0 ON "mydb"."default" DESTINATIONS ANY 'udp://h1.example.com:9090', 'udp://h2.example.com:9090';
```
### CREATE USER
```
create_user_stmt = "CREATE USER" user_name "WITH PASSWORD" password
[ "WITH ALL PRIVILEGES" ] .
```
#### Examples:
```sql
-- Create a normal database user.
CREATE USER jdoe WITH PASSWORD '1337password';
-- Create a cluster admin.
-- Note: Unlike the GRANT statement, the "PRIVILEGES" keyword is required here.
CREATE USER jdoe WITH PASSWORD '1337password' WITH ALL PRIVILEGES;
```
### DROP CONTINUOUS QUERY
```
drop_continuous_query_stmt = "DROP CONTINUOUS QUERY" query_name on_clause .
```
#### Example:
```sql
DROP CONTINUOUS QUERY myquery ON mydb;
```
### DROP DATABASE
```
drop_database_stmt = "DROP DATABASE" db_name .
```
#### Example:
```sql
DROP DATABASE mydb;
```
### DROP MEASUREMENT
```
drop_measurement_stmt = "DROP MEASUREMENT" measurement_name .
```
#### Examples:
```sql
-- drop the cpu measurement
DROP MEASUREMENT cpu;
```
### DROP RETENTION POLICY
```
drop_retention_policy_stmt = "DROP RETENTION POLICY" policy_name on_clause .
```
#### Example:
```sql
-- drop the retention policy named 1h.cpu from mydb
DROP RETENTION POLICY "1h.cpu" ON mydb;
```
### DROP SERIES
```
drop_series_stmt = "DROP SERIES" ( from_clause | where_clause | from_clause where_clause ) .
```
#### Example:
```sql
```
### DROP SUBSCRIPTION
```
drop_subscription_stmt = "DROP SUBSCRIPTION" subscription_name "ON" db_name "." retention_policy .
```
#### Example:
```sql
DROP SUBSCRIPTION sub0 ON "mydb"."default";
```
### DROP USER
```
drop_user_stmt = "DROP USER" user_name .
```
#### Example:
```sql
DROP USER jdoe;
```
### GRANT
NOTE: Users can be granted privileges on databases that do not exist.
```
grant_stmt = "GRANT" privilege [ on_clause ] to_clause .
```
#### Examples:
```sql
-- grant cluster admin privileges
GRANT ALL TO jdoe;
-- grant read access to a database
GRANT READ ON mydb TO jdoe;
```
### SHOW CONTINUOUS QUERIES
```
show_continuous_queries_stmt = "SHOW CONTINUOUS QUERIES" .
```
#### Example:
```sql
-- show all continuous queries
SHOW CONTINUOUS QUERIES;
```
### SHOW DATABASES
```
show_databases_stmt = "SHOW DATABASES" .
```
#### Example:
```sql
-- show all databases
SHOW DATABASES;
```
### SHOW FIELD KEYS
```
show_field_keys_stmt = "SHOW FIELD KEYS" [ from_clause ] .
```
#### Examples:
```sql
-- show field keys from all measurements
SHOW FIELD KEYS;
-- show field keys from specified measurement
SHOW FIELD KEYS FROM cpu;
```
### SHOW GRANTS
```
show_grants_stmt = "SHOW GRANTS FOR" user_name .
```
#### Example:
```sql
-- show grants for jdoe
SHOW GRANTS FOR jdoe;
```
### SHOW MEASUREMENTS
```
show_measurements_stmt = "SHOW MEASUREMENTS" [ with_measurement_clause ] [ where_clause ] [ limit_clause ] [ offset_clause ] .
```
```sql
-- show all measurements
SHOW MEASUREMENTS;
-- show measurements where region tag = 'uswest' AND host tag = 'serverA'
SHOW MEASUREMENTS WHERE region = 'uswest' AND host = 'serverA';
```
### SHOW RETENTION POLICIES
```
show_retention_policies = "SHOW RETENTION POLICIES" on_clause .
```
#### Example:
```sql
-- show all retention policies on a database
SHOW RETENTION POLICIES ON mydb;
```
### SHOW SERIES
```
show_series_stmt = "SHOW SERIES" [ from_clause ] [ where_clause ] [ limit_clause ] [ offset_clause ] .
```
#### Example:
```sql
```
### SHOW SHARD GROUPS
```
show_shard_groups_stmt = "SHOW SHARD GROUPS" .
```
#### Example:
```sql
SHOW SHARD GROUPS;
```
### SHOW SHARDS
```
show_shards_stmt = "SHOW SHARDS" .
```
#### Example:
```sql
SHOW SHARDS;
```
### SHOW SUBSCRIPTIONS
```
show_subscriptions_stmt = "SHOW SUBSCRIPTIONS" .
```
#### Example:
```sql
SHOW SUBSCRIPTIONS;
```
### SHOW TAG KEYS
```
show_tag_keys_stmt = "SHOW TAG KEYS" [ from_clause ] [ where_clause ] [ group_by_clause ]
[ limit_clause ] [ offset_clause ] .
```
#### Examples:
```sql
-- show all tag keys
SHOW TAG KEYS;
-- show all tag keys from the cpu measurement
SHOW TAG KEYS FROM cpu;
-- show all tag keys from the cpu measurement where the region key = 'uswest'
SHOW TAG KEYS FROM cpu WHERE region = 'uswest';
-- show all tag keys where the host key = 'serverA'
SHOW TAG KEYS WHERE host = 'serverA';
```
### SHOW TAG VALUES
```
show_tag_values_stmt = "SHOW TAG VALUES" [ from_clause ] with_tag_clause [ where_clause ]
[ group_by_clause ] [ limit_clause ] [ offset_clause ] .
```
#### Examples:
```sql
-- show all tag values across all measurements for the region tag
SHOW TAG VALUES WITH TAG = 'region';
-- show tag values from the cpu measurement for the region tag
SHOW TAG VALUES FROM cpu WITH KEY = 'region';
-- show tag values from the cpu measurement for region & host tag keys where service = 'redis'
SHOW TAG VALUES FROM cpu WITH KEY IN (region, host) WHERE service = 'redis';
```
### SHOW USERS
```
show_users_stmt = "SHOW USERS" .
```
#### Example:
```sql
-- show all users
SHOW USERS;
```
### REVOKE
```
revoke_stmt = "REVOKE" privilege [ on_clause ] "FROM" user_name .
```
#### Examples:
```sql
-- revoke cluster admin from jdoe
REVOKE ALL PRIVILEGES FROM jdoe;
-- revoke read privileges from jdoe on mydb
REVOKE READ ON mydb FROM jdoe;
```
### SELECT
```
select_stmt = "SELECT" fields from_clause [ into_clause ] [ where_clause ]
[ group_by_clause ] [ order_by_clause ] [ limit_clause ]
[ offset_clause ] [ slimit_clause ] [ soffset_clause ] .
```
#### Examples:
```sql
-- select mean value from the cpu measurement where region = 'uswest' grouped by 10 minute intervals
SELECT mean(value) FROM cpu WHERE region = 'uswest' GROUP BY time(10m) fill(0);
-- select from all measurements beginning with cpu into the same measurement name in the cpu_1h retention policy
SELECT mean(value) INTO cpu_1h.:MEASUREMENT FROM /cpu.*/
```
## Clauses
```
from_clause = "FROM" measurements .
group_by_clause = "GROUP BY" dimensions fill(fill_option).
into_clause = "INTO" ( measurement | back_ref ).
limit_clause = "LIMIT" int_lit .
offset_clause = "OFFSET" int_lit .
slimit_clause = "SLIMIT" int_lit .
soffset_clause = "SOFFSET" int_lit .
on_clause = "ON" db_name .
order_by_clause = "ORDER BY" sort_fields .
to_clause = "TO" user_name .
where_clause = "WHERE" expr .
with_measurement_clause = "WITH MEASUREMENT" ( "=" measurement | "=~" regex_lit ) .
with_tag_clause = "WITH KEY" ( "=" tag_key | "IN (" tag_keys ")" ) .
```
## Expressions
```
binary_op = "+" | "-" | "*" | "/" | "AND" | "OR" | "=" | "!=" | "<" |
"<=" | ">" | ">=" .
expr = unary_expr { binary_op unary_expr } .
unary_expr = "(" expr ")" | var_ref | time_lit | string_lit | int_lit |
float_lit | bool_lit | duration_lit | regex_lit .
```
## Other
```
alias = "AS" identifier .
back_ref = ( policy_name ".:MEASUREMENT" ) |
( db_name "." [ policy_name ] ".:MEASUREMENT" ) .
db_name = identifier .
dimension = expr .
dimensions = dimension { "," dimension } .
field_key = identifier .
field = expr [ alias ] .
fields = field { "," field } .
fill_option = "null" | "none" | "previous" | int_lit | float_lit .
host = string_lit .
measurement = measurement_name |
( policy_name "." measurement_name ) |
( db_name "." [ policy_name ] "." measurement_name ) .
measurements = measurement { "," measurement } .
measurement_name = identifier .
password = string_lit .
policy_name = identifier .
privilege = "ALL" [ "PRIVILEGES" ] | "READ" | "WRITE" .
query_name = identifier .
retention_policy = identifier .
retention_policy_option = retention_policy_duration |
retention_policy_replication |
"DEFAULT" .
retention_policy_duration = "DURATION" duration_lit .
retention_policy_replication = "REPLICATION" int_lit
series_id = int_lit .
sort_field = field_key [ ASC | DESC ] .
sort_fields = sort_field { "," sort_field } .
subscription_name = identifier .
tag_key = identifier .
tag_keys = tag_key { "," tag_key } .
user_name = identifier .
var_ref = measurement .
```
## Query Engine Internals
Once you understand the language itself, it's important to know how these
language constructs are implemented in the query engine. This gives you an
intuitive sense for how results will be processed and how to create efficient
queries.
The life cycle of a query looks like this:
1. InfluxQL query string is tokenized and then parsed into an abstract syntax
tree (AST). This is the code representation of the query itself.
2. The AST is passed to the `QueryExecutor` which directs queries to the
appropriate handlers. For example, queries related to meta data are executed
by the meta service and `SELECT` statements are executed by the shards
themselves.
3. The query engine then determines the shards that match the `SELECT`
statement's time range. From these shards, iterators are created for each
field in the statement.
4. Iterators are passed to the emitter which drains them and joins the resulting
points. The emitter's job is to convert simple time/value points into the
more complex result objects that are returned to the client.
### Understanding Iterators
Iterators are at the heart of the query engine. They provide a simple interface
for looping over a set of points. For example, this is an iterator over Float
points:
```
type FloatIterator interface {
Next() *FloatPoint
}
```
These iterators are created through the `IteratorCreator` interface:
```
type IteratorCreator interface {
CreateIterator(opt *IteratorOptions) (Iterator, error)
}
```
The `IteratorOptions` provide arguments about field selection, time ranges,
and dimensions that the iterator creator can use when planning an iterator.
The `IteratorCreator` interface is used at many levels such as the `Shards`,
`Shard`, and `Engine`. This allows optimizations to be performed when applicable
such as returning a precomputed `COUNT()`.
Iterators aren't just for reading raw data from storage though. Iterators can be
composed so that they provided additional functionality around an input
iterator. For example, a `DistinctIterator` can compute the distinct values for
each time window for an input iterator. Or a `FillIterator` can generate
additional points that are missing from an input iterator.
This composition also lends itself well to aggregation. For example, a statement
such as this:
```
SELECT MEAN(value) FROM cpu GROUP BY time(10m)
```
In this case, `MEAN(value)` is a `MeanIterator` wrapping an iterator from the
underlying shards. However, if we can add an additional iterator to determine
the derivative of the mean:
```
SELECT DERIVATIVE(MEAN(value), 20m) FROM cpu GROUP BY time(10m)
```
### Understanding Auxiliary Fields
Because InfluxQL allows users to use selector functions such as `FIRST()`,
`LAST()`, `MIN()`, and `MAX()`, the engine must provide a way to return related
data at the same time with the selected point.
For example, in this query:
```
SELECT FIRST(value), host FROM cpu GROUP BY time(1h)
```
We are selecting the first `value` that occurs every hour but we also want to
retrieve the `host` associated with that point. Since the `Point` types only
specify a single typed `Value` for efficiency, we push the `host` into the
auxiliary fields of the point. These auxiliary fields are attached to the point
until it is passed to the emitter where the fields get split off to their own
iterator.
### Built-in Iterators
There are many helper iterators that let us build queries:
* Merge Iterator - This iterator combines one or more iterators into a single
new iterator of the same type. This iterator guarantees that all points
within a window will be output before starting the next window but does not
provide ordering guarantees within the window. This allows for fast access
for aggregate queries which do not need stronger sorting guarantees.
* Sorted Merge Iterator - This iterator also combines one or more iterators
into a new iterator of the same type. However, this iterator guarantees
time ordering of every point. This makes it slower than the `MergeIterator`
but this ordering guarantee is required for non-aggregate queries which
return the raw data points.
* Limit Iterator - This iterator limits the number of points per name/tag
group. This is the implementation of the `LIMIT` & `OFFSET` syntax.
* Fill Iterator - This iterator injects extra points if they are missing from
the input iterator. It can provide `null` points, points with the previous
value, or points with a specific value.
* Buffered Iterator - This iterator provides the ability to "unread" a point
back onto a buffer so it can be read again next time. This is used extensively
to provide lookahead for windowing.
* Reduce Iterator - This iterator calls a reduction function for each point in
a window. When the window is complete then all points for that window are
output. This is used for simple aggregate functions such as `COUNT()`.
* Reduce Slice Iterator - This iterator collects all points for a window first
and then passes them all to a reduction function at once. The results are
returned from the iterator. This is used for aggregate functions such as
`DERIVATIVE()`.
* Transform Iterator - This iterator calls a transform function for each point
from an input iterator. This is used for executing binary expressions.
* Dedupe Iterator - This iterator only outputs unique points. It is resource
intensive so it is only used for small queries such as meta query statements.
### Call Iterators
Function calls in InfluxQL are implemented at two levels. Some calls can be
wrapped at multiple layers to improve efficiency. For example, a `COUNT()` can
be performed at the shard level and then multiple `CountIterator`s can be
wrapped with another `CountIterator` to compute the count of all shards. These
iterators can be created using `NewCallIterator()`.
Some iterators are more complex or need to be implemented at a higher level.
For example, the `DERIVATIVE()` needs to retrieve all points for a window first
before performing the calculation. This iterator is created by the engine itself
and is never requested to be created by the lower levels.
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