SQL
GreptimeDB supports full SQL for querying data from a database.
In this document, we will use the monitor
table to demonstrate how to query data. For instructions on creating the monitor
table and inserting data into it, please refer to Table Management and Write Data.
Basic query
The query is represented by the SELECT
statement. For example, the following query selects all data from the monitor
table:
sql
SELECT * FROM monitor;
The query result looks like the following:
sql
+-----------+---------------------+------+--------+
| host | ts | cpu | memory |
+-----------+---------------------+------+--------+
| 127.0.0.1 | 2022-11-03 03:39:57 | 0.1 | 0.4 |
| 127.0.0.1 | 2022-11-03 03:39:58 | 0.5 | 0.2 |
| 127.0.0.2 | 2022-11-03 03:39:58 | 0.2 | 0.3 |
+-----------+---------------------+------+--------+
3 rows in set (0.00 sec)
Functions are also supported in the SELECT
field list. For example, you can use the count()
function to retrieve the total number of rows in the table:
sql
SELECT count(*) FROM monitor;
sql
+-----------------+
| COUNT(UInt8(1)) |
+-----------------+
| 3 |
+-----------------+
The avg()
function returns the average value of a certain field:
sql
SELECT avg(cpu) FROM monitor;
sql
+---------------------+
| AVG(monitor.cpu) |
+---------------------+
| 0.26666666666666666 |
+---------------------+
1 row in set (0.00 sec)
You can also select only the result of a function. For example, you can extract the day of the year from a timestamp. The DOY
in the SQL statement is the abbreviation of day of the year
:
sql
SELECT date_part('DOY', '2021-07-01 00:00:00');
Output:
sql
+----------------------------------------------------+
| date_part(Utf8("DOY"),Utf8("2021-07-01 00:00:00")) |
+----------------------------------------------------+
| 182 |
+----------------------------------------------------+
1 row in set (0.003 sec)
Please refer to SELECT and Functions for more information.
Limit the number of rows returned
Time series data is typically massive. To save bandwidth and improve query performance, you can use the LIMIT
clause to restrict the number of rows returned by the SELECT
statement.
For example, the following query limits the number of rows returned to 10:
sql
SELECT * FROM monitor LIMIT 10;
Filter data
You can use the WHERE
clause to filter the rows returned by the SELECT
statement.
Filtering data by tags or time index is efficient and common in time series scenarios. For example, the following query filter data by tag host
:
sql
SELECT * FROM monitor WHERE host='127.0.0.1';
The following query filter data by time index ts
, and returns the data after 2022-11-03 03:39:57
:
sql
SELECT * FROM monitor WHERE ts > '2022-11-03 03:39:57';
You can also use the AND
keyword to combine multiple constraints:
sql
SELECT * FROM monitor WHERE host='127.0.0.1' AND ts > '2022-11-03 03:39:57';
Filter by time index
Filtering data by the time index is a crucial feature in time series databases.
When working with Unix time values, the database treats them based on the type of the column value. For instance, if the ts
column in the monitor
table has a value type of TimestampMillisecond
, you can use the following query to filter the data:
The Unix time value 1667446797000
corresponds to the TimestampMillisecond
type。
sql
SELECT * FROM monitor WHERE ts > 1667446797000;
When working with a Unix time value that doesn’t have the precision of the column value, you need to use the ::
syntax to specify the type of the time value. This ensures that the database correctly identifies the type.
For example, 1667446797
represents a timestamp in seconds, which is different from the default millisecond timestamp of the ts
column. You need to specify its type as TimestampSecond
using the ::TimestampSecond
syntax. This informs the database that the value 1667446797
should be treated as a timestamp in seconds.
sql
select * from monitor where ts > 1667446797::TimestampSecond;
When using standard RFC3339
or ISO8601
string literals, you can directly use them in the filter condition since the precision is clear:
sql
select * from monitor where ts > '2022-07-25 10:32:16.408';
Time and date functions are also supported in the filter condition. For example, use the now()
function and the INTERVAL
keyword to retrieve data from the last 5 minutes:
sql
SELECT * from monitor WHERE ts >= now() - INTERVAL '5 minutes';
For date and time functions, please refer to Functions for more information.
Order By
The order of the returned data is not guaranteed. You need to use the ORDER BY
clause to sort the returned data. For example, in time series scenarios, it is common to use the time index column as the sorting key to arrange the data chronologically:
sql
-- ascending order by ts
SELECT * FROM monitor ORDER BY ts ASC;
sql
-- descending order by ts
SELECT * FROM monitor ORDER BY ts DESC;
Aggregate data by tag
You can use the GROUP BY
clause to group rows that have the same values into summary rows. The average memory usage grouped by idc:
sql
SELECT host, avg(cpu) FROM monitor GROUP BY host;
sql
+-----------+------------------+
| host | AVG(monitor.cpu) |
+-----------+------------------+
| 127.0.0.2 | 0.2 |
| 127.0.0.1 | 0.3 |
+-----------+------------------+
2 rows in set (0.00 sec)
Please refer to GROUP BY for more information.
Aggregate data by time window
GreptimeDB supports Range Query to aggregate data by time window.
Suppose we have the following data in the monitor table:
sql
+-----------+---------------------+------+--------+
| host | ts | cpu | memory |
+-----------+---------------------+------+--------+
| 127.0.0.1 | 2023-12-13 02:05:41 | 0.5 | 0.2 |
| 127.0.0.1 | 2023-12-13 02:05:46 | NULL | NULL |
| 127.0.0.1 | 2023-12-13 02:05:51 | 0.4 | 0.3 |
| 127.0.0.2 | 2023-12-13 02:05:41 | 0.3 | 0.1 |
| 127.0.0.2 | 2023-12-13 02:05:46 | NULL | NULL |
| 127.0.0.2 | 2023-12-13 02:05:51 | 0.2 | 0.4 |
+-----------+---------------------+------+--------+
The following query returns the average CPU usage in a 10-second time range and calculates it every 5 seconds:
sql
SELECT
ts,
host,
avg(cpu) RANGE '10s' FILL LINEAR
FROM monitor
ALIGN '5s' TO '2023-12-01T00:00:00' BY (host) ORDER BY ts ASC;
avg(cpu) RANGE '10s' FILL LINEAR
is a Range expression.RANGE '10s'
specifies that the time range of the aggregation is 10s, andFILL LINEAR
specifies that if there is no data within a certain aggregation time, use theLINEAR
method to fill it.ALIGN '5s'
specifies the that data statistics should be performed in steps of 5s.TO '2023-12-01T00:00:00
specifies the origin alignment time. The default value is Unix time 0.BY (host)
specifies the aggregate key. If theBY
keyword is omitted, the primary key of the data table is used as the aggregate key by default.ORDER BY ts ASC
specifies the sorting method of the result set. If you do not specify the sorting method, the order of the results is not guaranteed.
The Response is shown below:
sql
+---------------------+-----------+----------------------------------------+
| ts | host | AVG(monitor.cpu) RANGE 10s FILL LINEAR |
+---------------------+-----------+----------------------------------------+
| 2023-12-13 02:05:35 | 127.0.0.1 | 0.5 |
| 2023-12-13 02:05:40 | 127.0.0.1 | 0.5 |
| 2023-12-13 02:05:45 | 127.0.0.1 | 0.4 |
| 2023-12-13 02:05:50 | 127.0.0.1 | 0.4 |
| 2023-12-13 02:05:35 | 127.0.0.2 | 0.3 |
| 2023-12-13 02:05:40 | 127.0.0.2 | 0.3 |
| 2023-12-13 02:05:45 | 127.0.0.2 | 0.2 |
| 2023-12-13 02:05:50 | 127.0.0.2 | 0.2 |
+---------------------+-----------+----------------------------------------+
Time range window
The origin time range window steps forward and backward in the time series to generate all time range windows. In the example above, the origin alignment time is set to 2023-12-01T00:00:00
, which is also the end time of the origin time window.
The RANGE
option, along with the origin alignment time, defines the origin time range window that starts from origin alignment timestamp
and ends at origin alignment timestamp + range
.
The ALIGN
option defines the query resolution steps. It determines the calculation steps from the origin time window to other time windows. For example, with the origin alignment time 2023-12-01T00:00:00
and ALIGN '5s'
, the alignment times are 2023-11-30T23:59:55
, 2023-12-01T00:00:00
, 2023-12-01T00:00:05
, 2023-12-01T00:00:10
, and so on.
These time windows are left-closed and right-open intervals that satisfy the condition [alignment timestamp, alignment timestamp + range)
.
The following images can help you understand the time range window more visually:
When the query resolution is greater than the time range window, the metrics data will be calculated for only one time range window.
When the query resolution is less than the time range window, the metrics data will be calculated for multiple time range windows.
Align to specific timestamp
You can change the origin alignment time to any timestamp you want. For example, use NOW
to align to the current time:
sql
SELECT
ts,
host,
avg(cpu) RANGE '1w'
FROM monitor
ALIGN '1d' TO NOW BY (host);
Or use a ISO 8601
timestamp to align to a specified time:
sql
SELECT
ts,
host,
avg(cpu) RANGE '1w'
FROM monitor
ALIGN '1d' TO '2023-12-01T00:00:00+08:00' BY (host);
Fill null values
The FILL
option can be used to fill null values in the data. In the above example, the LINEAR
method is used to fill null values. Other methods are also supported, such as PREV
and a constant value X
. For more information, please refer to the FILL OPTION.
Syntax
Please refer to Range Query for more information.
HTTP API
Use POST method to query data:
shell
curl -X POST \
-H 'authorization: Basic {{authorization if exists}}' \
-H 'Content-Type: application/x-www-form-urlencoded' \
-d 'sql=select * from monitor' \
http://localhost:4000/v1/sql?db=public
The result is shown below:
json
{
"code": 0,
"output": [
{
"records": {
"schema": {
"column_schemas": [
{
"name": "host",
"data_type": "String"
},
{
"name": "ts",
"data_type": "TimestampMillisecond"
},
{
"name": "cpu",
"data_type": "Float64"
},
{
"name": "memory",
"data_type": "Float64"
}
]
},
"rows": [
["127.0.0.1", 1667446797450, 0.1, 0.4],
["127.0.0.1", 1667446798450, 0.5, 0.2],
["127.0.0.2", 1667446798450, 0.2, 0.3]
]
}
}
],
"execution_time_ms": 0
}
For more information about SQL HTTP request, please refer to API document.