Timeseries Management

July 14, 2023About 19 min

Timeseries Management

Database Management

Create Database

According to the storage model we can set up the corresponding database. Two SQL statements are supported for creating databases, as follows:

IoTDB > create database root.ln
IoTDB > create database root.sgcc

We can thus create two databases using the above two SQL statements.

It is worth noting that 1 database is recommended.

When the path itself or the parent/child layer of the path is already created as database, the path is then not allowed to be created as database. For example, it is not feasible to create root.ln.wf01 as database when two databases root.ln and root.sgcc exist. The system gives the corresponding error prompt as shown below:

IoTDB> CREATE DATABASE root.ln.wf01
Msg: 300: root.ln has already been created as database.
IoTDB> create database root.ln.wf01
Msg: 300: root.ln has already been created as database.

The LayerName of database can only be chinese or english characters, numbers, underscores, dots and backticks. If you want to set it to pure numbers or contain backticks or dots, you need to enclose the database name with backticks (``). In ``，2 backticks represents one, i.e. ```` represents `.

Besides, if deploy on Windows system, the LayerName is case-insensitive, which means it's not allowed to create databases root.ln and root.LN at the same time.

Show Databases

After creating the database, we can use the SHOW DATABASES statement and SHOW DATABASES <PathPattern> to view the databases. The SQL statements are as follows:

IoTDB> SHOW DATABASES
IoTDB> SHOW DATABASES root.**

The result is as follows:

+-------------+----+-------------------------+-----------------------+-----------------------+
|database| ttl|schema_replication_factor|data_replication_factor|time_partition_interval|
+-------------+----+-------------------------+-----------------------+-----------------------+
|    root.sgcc|null|                        2|                      2|                 604800|
|      root.ln|null|                        2|                      2|                 604800|
+-------------+----+-------------------------+-----------------------+-----------------------+
Total line number = 2
It costs 0.060s

Delete Database

User can use the DELETE DATABASE <PathPattern> statement to delete all databases matching the pathPattern. Please note the data in the database will also be deleted.

IoTDB > DELETE DATABASE root.ln
IoTDB > DELETE DATABASE root.sgcc
// delete all data, all timeseries and all databases
IoTDB > DELETE DATABASE root.**

Count Databases

User can use the COUNT DATABASE <PathPattern> statement to count the number of databases. It is allowed to specify PathPattern to count the number of databases matching the PathPattern.

SQL statement is as follows:

IoTDB> count databases
IoTDB> count databases root.*
IoTDB> count databases root.sgcc.*
IoTDB> count databases root.sgcc

The result is as follows:

+-------------+
|     database|
+-------------+
|    root.sgcc|
| root.turbine|
|      root.ln|
+-------------+
Total line number = 3
It costs 0.003s

+-------------+
|     database|
+-------------+
|            3|
+-------------+
Total line number = 1
It costs 0.003s

+-------------+
|     database|
+-------------+
|            3|
+-------------+
Total line number = 1
It costs 0.002s

+-------------+
|     database|
+-------------+
|            0|
+-------------+
Total line number = 1
It costs 0.002s

+-------------+
|     database|
+-------------+
|            1|
+-------------+
Total line number = 1
It costs 0.002s

Setting up heterogeneous databases (Advanced operations)

Under the premise of familiar with IoTDB metadata modeling, users can set up heterogeneous databases in IoTDB to cope with different production needs.

Currently, the following database heterogeneous parameters are supported:

Parameter	Type	Description
TTL	Long	TTL of the Database
SCHEMA_REPLICATION_FACTOR	Integer	The schema replication number of the Database
DATA_REPLICATION_FACTOR	Integer	The data replication number of the Database
SCHEMA_REGION_GROUP_NUM	Integer	The SchemaRegionGroup number of the Database
DATA_REGION_GROUP_NUM	Integer	The DataRegionGroup number of the Database

Note the following when configuring heterogeneous parameters:

TTL and TIME_PARTITION_INTERVAL must be positive integers.
SCHEMA_REPLICATION_FACTOR and DATA_REPLICATION_FACTOR must be smaller than or equal to the number of deployed DataNodes.
The function of SCHEMA_REGION_GROUP_NUM and DATA_REGION_GROUP_NUM are related to the parameter schema_region_group_extension_policy and data_region_group_extension_policy in iotdb-common.properties configuration file. Take DATA_REGION_GROUP_NUM as an example: If data_region_group_extension_policy=CUSTOM is set, DATA_REGION_GROUP_NUM serves as the number of DataRegionGroups owned by the Database. If data_region_group_extension_policy=AUTO, DATA_REGION_GROUP_NUM is used as the lower bound of the DataRegionGroup quota owned by the Database. That is, when the Database starts writing data, it will have at least this number of DataRegionGroups.

Users can set any heterogeneous parameters when creating a Database, or adjust some heterogeneous parameters during a stand-alone/distributed IoTDB run.

Set heterogeneous parameters when creating a Database

The user can set any of the above heterogeneous parameters when creating a Database. The SQL statement is as follows:

CREATE DATABASE prefixPath (WITH databaseAttributeClause (COMMA? databaseAttributeClause)*)?

For example:

CREATE DATABASE root.db WITH SCHEMA_REPLICATION_FACTOR=1, DATA_REPLICATION_FACTOR=3, SCHEMA_REGION_GROUP_NUM=1, DATA_REGION_GROUP_NUM=2;

Adjust heterogeneous parameters at run time

Users can adjust some heterogeneous parameters during the IoTDB runtime, as shown in the following SQL statement:

ALTER DATABASE prefixPath WITH databaseAttributeClause (COMMA? databaseAttributeClause)*

For example:

ALTER DATABASE root.db WITH SCHEMA_REGION_GROUP_NUM=1, DATA_REGION_GROUP_NUM=2;

Note that only the following heterogeneous parameters can be adjusted at runtime:

SCHEMA_REGION_GROUP_NUM
DATA_REGION_GROUP_NUM

Show heterogeneous databases

The user can query the specific heterogeneous configuration of each Database, and the SQL statement is as follows:

SHOW DATABASES DETAILS prefixPath?

For example:

IoTDB> SHOW DATABASES DETAILS
+--------+--------+-----------------------+---------------------+---------------------+--------------------+-----------------------+-----------------------+------------------+---------------------+---------------------+
|Database|     TTL|SchemaReplicationFactor|DataReplicationFactor|TimePartitionInterval|SchemaRegionGroupNum|MinSchemaRegionGroupNum|MaxSchemaRegionGroupNum|DataRegionGroupNum|MinDataRegionGroupNum|MaxDataRegionGroupNum|
+--------+--------+-----------------------+---------------------+---------------------+--------------------+-----------------------+-----------------------+------------------+---------------------+---------------------+
|root.db1|    null|                      1|                    3|            604800000|                   0|                      1|                      1|                 0|                    2|                    2|
|root.db2|86400000|                      1|                    1|            604800000|                   0|                      1|                      1|                 0|                    2|                    2|
|root.db3|    null|                      1|                    1|            604800000|                   0|                      1|                      1|                 0|                    2|                    2|
+--------+--------+-----------------------+---------------------+---------------------+--------------------+-----------------------+-----------------------+------------------+---------------------+---------------------+
Total line number = 3
It costs 0.058s

The query results in each column are as follows:

The name of the Database
The TTL of the Database
The schema replication number of the Database
The data replication number of the Database
The time partition interval of the Database
The current SchemaRegionGroup number of the Database
The required minimum SchemaRegionGroup number of the Database
The permitted maximum SchemaRegionGroup number of the Database
The current DataRegionGroup number of the Database
The required minimum DataRegionGroup number of the Database
The permitted maximum DataRegionGroup number of the Database

TTL

IoTDB supports device-level TTL settings, which means it is able to delete old data automatically and periodically. The benefit of using TTL is that hopefully you can control the total disk space usage and prevent the machine from running out of disks. Moreover, the query performance may downgrade as the total number of files goes up and the memory usage also increases as there are more files. Timely removing such files helps to keep at a high query performance level and reduce memory usage.

The default unit of TTL is milliseconds. If the time precision in the configuration file changes to another, the TTL is still set to milliseconds.

When setting TTL, the system will look for all devices included in the set path and set TTL for these devices. The system will delete expired data at the device granularity. After the device data expires, it will not be queryable. The data in the disk file cannot be guaranteed to be deleted immediately, but it can be guaranteed to be deleted eventually. However, due to operational costs, the expired data will not be physically deleted right after expiring. The physical deletion is delayed until compaction. Therefore, before the data is physically deleted, if the TTL is reduced or lifted, it may cause data that was previously invisible due to TTL to reappear. The system can only set up to 1000 TTL rules, and when this limit is reached, some TTL rules need to be deleted before new rules can be set.

TTL Path Rule

The path can only be prefix paths (i.e., the path cannot contain * , except ** in the last level). This path will match devices and also allows users to specify paths without asterisks as specific databases or devices. When the path does not contain asterisks, the system will check if it matches a database; if it matches a database, both the path and path.** will be set at the same time. Note: Device TTL settings do not verify the existence of metadata, i.e., it is allowed to set TTL for a non-existent device.

qualified paths：
root.**
root.db.**
root.db.group1.**
root.db
root.db.group1.d1

unqualified paths：
root.*.db
root.**.db.*
root.db.*

TTL Applicable Rules

When a device is subject to multiple TTL rules, the more precise and longer rules are prioritized. For example, for the device "root.bj.hd.dist001.turbine001", the rule "root.bj.hd.dist001.turbine001" takes precedence over "root.bj.hd.dist001.**", and the rule "root.bj.hd.dist001.**" takes precedence over "root.bj.hd.**".

Set TTL

The set ttl operation can be understood as setting a TTL rule, for example, setting ttl to root.sg.group1.** is equivalent to mounting ttl for all devices that can match this path pattern. The unset ttl operation indicates unmounting TTL for the corresponding path pattern; if there is no corresponding TTL, nothing will be done. If you want to set TTL to be infinitely large, you can use the INF keyword. The SQL Statement for setting TTL is as follow:

set ttl to pathPattern 360000;

Set the Time to Live (TTL) to a pathPattern of 360,000 milliseconds; the pathPattern should not contain a wildcard (*) in the middle and must end with a double asterisk (**). The pathPattern is used to match corresponding devices. To maintain compatibility with older SQL syntax, if the user-provided pathPattern matches a database (db), the path pattern is automatically expanded to include all sub-paths denoted by path.**. For instance, writing "set ttl to root.sg 360000" will automatically be transformed into "set ttl to root.sg.** 360000", which sets the TTL for all devices under root.sg. However, if the specified pathPattern does not match a database, the aforementioned logic will not apply. For example, writing "set ttl to root.sg.group 360000" will not be expanded to "root.sg.group.**" since root.sg.group does not match a database. It is also permissible to specify a particular device without a wildcard (*).

Unset TTL

To unset TTL, we can use follwing SQL statement:

IoTDB> unset ttl from root.ln

After unset TTL, all data will be accepted in root.ln.

IoTDB> unset ttl from root.sgcc.**

Unset the TTL in the root.sgcc path.

New syntax

IoTDB> unset ttl from root.**

Old syntax

IoTDB> unset ttl to root.**

There is no functional difference between the old and new syntax, and they are compatible with each other. The new syntax is just more conventional in terms of wording.

Unset the TTL setting for all path pattern.

Show TTL

To Show TTL, we can use following SQL statement:

show all ttl

IoTDB> SHOW ALL TTL
+--------------+--------+
|          path|     TTL|
|       root.**|55555555|
| root.sg2.a.**|44440000|
+--------------+--------+

show ttl on pathPattern

IoTDB> SHOW TTL ON root.db.**;
+--------------+--------+
|          path|     TTL|
|    root.db.**|55555555|
|  root.db.a.**|44440000|
+--------------+--------+

The SHOW ALL TTL example gives the TTL for all path patterns. The SHOW TTL ON pathPattern shows the TTL for the path pattern specified.

Display devices' ttl

IoTDB> show devices
+---------------+---------+---------+
|         Device|IsAligned|      TTL|
+---------------+---------+---------+
|root.sg.device1|    false| 36000000|
|root.sg.device2|     true|      INF|
+---------------+---------+---------+

All devices will definitely have a TTL, meaning it cannot be null. INF represents infinity.

Device Template

IoTDB supports the device template function, enabling different entities of the same type to share metadata, reduce the memory usage of metadata, and simplify the management of numerous entities and measurements.

Create Device Template

The SQL syntax for creating a metadata template is as follows:

CREATE DEVICE TEMPLATE <templateName> ALIGNED? '(' <measurementId> <attributeClauses> [',' <measurementId> <attributeClauses>]+ ')'

Example 1: Create a template containing two non-aligned timeseries

IoTDB> create device template t1 (temperature FLOAT encoding=RLE, status BOOLEAN encoding=PLAIN compression=SNAPPY)

Example 2: Create a template containing a group of aligned timeseries

IoTDB> create device template t2 aligned (lat FLOAT encoding=Gorilla, lon FLOAT encoding=Gorilla)

The lat and lon measurements are aligned.

Set Device Template

After a device template is created, it should be set to specific path before creating related timeseries or insert data.

It should be ensured that the related database has been set before setting template.

It is recommended to set device template to database path. It is not suggested to set device template to some path above database

It is forbidden to create timeseries under a path setting s tedeviceplate. Device template shall not be set on a prefix path of an existing timeseries.

The SQL Statement for setting device template is as follow:

IoTDB> set device template t1 to root.sg1.d1

Activate Device Template

After setting the device template, with the system enabled to auto create schema, you can insert data into the timeseries. For example, suppose there's a database root.sg1 and t1 has been set to root.sg1.d1, then timeseries like root.sg1.d1.temperature and root.sg1.d1.status are available and data points can be inserted.

Attention: Before inserting data or the system not enabled to auto create schema, timeseries defined by the device template will not be created. You can use the following SQL statement to create the timeseries or activate the templdeviceate, act before inserting data:

IoTDB> create timeseries using device template on root.sg1.d1

Example: Execute the following statement

IoTDB> set device template t1 to root.sg1.d1
IoTDB> set device template t2 to root.sg1.d2
IoTDB> create timeseries using device template on root.sg1.d1
IoTDB> create timeseries using device template on root.sg1.d2

Show the time series:

show timeseries root.sg1.**

+-----------------------+-----+-------------+--------+--------+-----------+----+----------+--------+-------------------+
|             timeseries|alias|     database|dataType|encoding|compression|tags|attributes|deadband|deadband parameters|
+-----------------------+-----+-------------+--------+--------+-----------+----+----------+--------+-------------------+
|root.sg1.d1.temperature| null|     root.sg1|   FLOAT|     RLE|     SNAPPY|null|      null|    null|               null|
|     root.sg1.d1.status| null|     root.sg1| BOOLEAN|   PLAIN|     SNAPPY|null|      null|    null|               null|
|        root.sg1.d2.lon| null|     root.sg1|   FLOAT| GORILLA|     SNAPPY|null|      null|    null|               null|
|        root.sg1.d2.lat| null|     root.sg1|   FLOAT| GORILLA|     SNAPPY|null|      null|    null|               null|
+-----------------------+-----+-------------+--------+--------+-----------+----+----------+--------+-------------------+

Show the devices:

show devices root.sg1.**

+---------------+---------+
|        devices|isAligned|
+---------------+---------+
|    root.sg1.d1|    false|
|    root.sg1.d2|     true|
+---------------+---------+

Show Device Template

Show all device templates

The SQL statement looks like this:

IoTDB> show device templates

The execution result is as follows:

+-------------+
|template name|
+-------------+
|           t2|
|           t1|
+-------------+

Show nodes under in device template

The SQL statement looks like this:

IoTDB> show nodes in device template t1

The execution result is as follows:

+-----------+--------+--------+-----------+
|child nodes|dataType|encoding|compression|
+-----------+--------+--------+-----------+
|temperature|   FLOAT|     RLE|     SNAPPY|
|     status| BOOLEAN|   PLAIN|     SNAPPY|
+-----------+--------+--------+-----------+

Show the path prefix where a device template is set

IoTDB> show paths set device template t1

The execution result is as follows:

+-----------+
|child paths|
+-----------+
|root.sg1.d1|
+-----------+

Show the path prefix where a device template is used (i.e. the time series has been created)

IoTDB> show paths using device template t1

The execution result is as follows:

+-----------+
|child paths|
+-----------+
|root.sg1.d1|
+-----------+

Deactivate device Template

To delete a group of timeseries represented by device template, namely deactivate the device template, use the following SQL statement:

IoTDB> delete timeseries of device template t1 from root.sg1.d1

IoTDB> deactivate device template t1 from root.sg1.d1

The deactivation supports batch process.

IoTDB> delete timeseries of device template t1 from root.sg1.*, root.sg2.*

IoTDB> deactivate device template t1 from root.sg1.*, root.sg2.*

If the template name is not provided in sql, all template activation on paths matched by given path pattern will be removed.

Unset Device Template

The SQL Statement for unsetting device template is as follow:

IoTDB> unset device template t1 from root.sg1.d1

Attention: It should be guaranteed that none of the timeseries represented by the target device template exists, before unset it. It can be achieved by deactivation operation.

Drop Device Template

The SQL Statement for dropping device template is as follow:

IoTDB> drop device template t1

Attention: Dropping an already set template is not supported.

Alter Device Template

In a scenario where measurements need to be added, you can modify the template to add measurements to all devicesdevice using the device template.

The SQL Statement for altering device template is as follow:

IoTDB> alter device template t1 add (speed FLOAT encoding=RLE, FLOAT TEXT encoding=PLAIN compression=SNAPPY)

When executing data insertion to devices with device template set on related prefix path and there are measurements not present in this device template, the measurements will be auto added to this device template.

Timeseries Management

Create Timeseries

According to the storage model selected before, we can create corresponding timeseries in the two databases respectively. The SQL statements for creating timeseries are as follows:

IoTDB > create timeseries root.ln.wf01.wt01.status with datatype=BOOLEAN,encoding=PLAIN
IoTDB > create timeseries root.ln.wf01.wt01.temperature with datatype=FLOAT,encoding=RLE
IoTDB > create timeseries root.ln.wf02.wt02.hardware with datatype=TEXT,encoding=PLAIN
IoTDB > create timeseries root.ln.wf02.wt02.status with datatype=BOOLEAN,encoding=PLAIN
IoTDB > create timeseries root.sgcc.wf03.wt01.status with datatype=BOOLEAN,encoding=PLAIN
IoTDB > create timeseries root.sgcc.wf03.wt01.temperature with datatype=FLOAT,encoding=RLE

From v0.13, you can use a simplified version of the SQL statements to create timeseries:

IoTDB > create timeseries root.ln.wf01.wt01.status BOOLEAN encoding=PLAIN
IoTDB > create timeseries root.ln.wf01.wt01.temperature FLOAT encoding=RLE
IoTDB > create timeseries root.ln.wf02.wt02.hardware TEXT encoding=PLAIN
IoTDB > create timeseries root.ln.wf02.wt02.status BOOLEAN encoding=PLAIN
IoTDB > create timeseries root.sgcc.wf03.wt01.status BOOLEAN encoding=PLAIN
IoTDB > create timeseries root.sgcc.wf03.wt01.temperature FLOAT encoding=RLE

Notice that when in the CREATE TIMESERIES statement the encoding method conflicts with the data type, the system gives the corresponding error prompt as shown below:

IoTDB > create timeseries root.ln.wf02.wt02.status WITH DATATYPE=BOOLEAN, ENCODING=TS_2DIFF
error: encoding TS_2DIFF does not support BOOLEAN

Please refer to Encoding for correspondence between data type and encoding.

Create Aligned Timeseries

The SQL statement for creating a group of timeseries are as follows:

IoTDB> CREATE ALIGNED TIMESERIES root.ln.wf01.GPS(latitude FLOAT encoding=PLAIN compressor=SNAPPY, longitude FLOAT encoding=PLAIN compressor=SNAPPY)

You can set different datatype, encoding, and compression for the timeseries in a group of aligned timeseries

It is also supported to set an alias, tag, and attribute for aligned timeseries.

Delete Timeseries

To delete the timeseries we created before, we are able to use (DELETE | DROP) TimeSeries <PathPattern> statement.

The usage are as follows:

IoTDB> delete timeseries root.ln.wf01.wt01.status
IoTDB> delete timeseries root.ln.wf01.wt01.temperature, root.ln.wf02.wt02.hardware
IoTDB> delete timeseries root.ln.wf02.*
IoTDB> drop timeseries root.ln.wf02.*

Show Timeseries

SHOW LATEST? TIMESERIES pathPattern? whereClause? limitClause?
There are four optional clauses added in SHOW TIMESERIES, return information of time series

Timeseries information includes: timeseries path, alias of measurement, database it belongs to, data type, encoding type, compression type, tags and attributes.

Examples:

SHOW TIMESERIES
presents all timeseries information in JSON form
SHOW TIMESERIES <PathPattern>
returns all timeseries information matching the given <PathPattern>. SQL statements are as follows:

IoTDB> show timeseries root.**
IoTDB> show timeseries root.ln.**

The results are shown below respectively:

+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
|                     timeseries|   alias|     database|dataType|encoding|compression|                                       tags|                                              attributes|deadband|deadband parameters|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
|root.sgcc.wf03.wt01.temperature|    null|    root.sgcc|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|    null|               null|
|     root.sgcc.wf03.wt01.status|    null|    root.sgcc| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|    null|               null|
|             root.turbine.d1.s1|newAlias| root.turbine|   FLOAT|     RLE|     SNAPPY|{"newTag1":"newV1","tag4":"v4","tag3":"v3"}|{"attr2":"v2","attr1":"newV1","attr4":"v4","attr3":"v3"}|    null|               null|
|     root.ln.wf02.wt02.hardware|    null|      root.ln|    TEXT|   PLAIN|     SNAPPY|                                       null|                                                    null|    null|               null|
|       root.ln.wf02.wt02.status|    null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|    null|               null|
|  root.ln.wf01.wt01.temperature|    null|      root.ln|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|    null|               null|
|       root.ln.wf01.wt01.status|    null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|    null|               null|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
Total line number = 7
It costs 0.016s

+-----------------------------+-----+-------------+--------+--------+-----------+----+----------+--------+-------------------+
|                   timeseries|alias|     database|dataType|encoding|compression|tags|attributes|deadband|deadband parameters|
+-----------------------------+-----+-------------+--------+--------+-----------+----+----------+--------+-------------------+
|   root.ln.wf02.wt02.hardware| null|      root.ln|    TEXT|   PLAIN|     SNAPPY|null|      null|    null|               null|
|     root.ln.wf02.wt02.status| null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|null|      null|    null|               null|
|root.ln.wf01.wt01.temperature| null|      root.ln|   FLOAT|     RLE|     SNAPPY|null|      null|    null|               null|
|     root.ln.wf01.wt01.status| null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|null|      null|    null|               null|
+-----------------------------+-----+-------------+--------+--------+-----------+----+----------+--------+-------------------+
Total line number = 4
It costs 0.004s

SHOW TIMESERIES LIMIT INT OFFSET INT
returns all the timeseries information start from the offset and limit the number of series returned. For example,

show timeseries root.ln.** limit 10 offset 10

SHOW TIMESERIES WHERE TIMESERIES contains 'containStr'
The query result set is filtered by string fuzzy matching based on the names of the timeseries. For example:

show timeseries root.ln.** where timeseries contains 'wf01.wt'

The result is shown below:

+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
|                     timeseries|   alias|     database|dataType|encoding|compression|                                       tags|                                              attributes|deadband|deadband parameters|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
|  root.ln.wf01.wt01.temperature|    null|      root.ln|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|    null|               null|
|       root.ln.wf01.wt01.status|    null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|    null|               null|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
Total line number = 2
It costs 0.016s

SHOW TIMESERIES WHERE DataType=type
The query result set is filtered by data type. For example:

show timeseries root.ln.** where dataType=FLOAT

The result is shown below:

+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
|                     timeseries|   alias|     database|dataType|encoding|compression|                                       tags|                                              attributes|deadband|deadband parameters|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
|root.sgcc.wf03.wt01.temperature|    null|    root.sgcc|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|    null|               null|
|             root.turbine.d1.s1|newAlias| root.turbine|   FLOAT|     RLE|     SNAPPY|{"newTag1":"newV1","tag4":"v4","tag3":"v3"}|{"attr2":"v2","attr1":"newV1","attr4":"v4","attr3":"v3"}|    null|               null|
|  root.ln.wf01.wt01.temperature|    null|      root.ln|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|    null|               null|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
Total line number = 3
It costs 0.016s

SHOW LATEST TIMESERIES
all the returned timeseries information should be sorted in descending order of the last timestamp of timeseries

It is worth noting that when the queried path does not exist, the system will return no timeseries.

Count Timeseries

IoTDB is able to use COUNT TIMESERIES <Path> to count the number of timeseries matching the path. SQL statements are as follows:

WHERE condition could be used to fuzzy match a time series name with the following syntax: COUNT TIMESERIES <Path> WHERE TIMESERIES contains 'containStr'.
WHERE condition could be used to filter result by data type with the syntax: COUNT TIMESERIES <Path> WHERE DataType=<DataType>'.
WHERE condition could be used to filter result by tags with the syntax: COUNT TIMESERIES <Path> WHERE TAGS(key)='value' or COUNT TIMESERIES <Path> WHERE TAGS(key) contains 'value'.
LEVEL could be defined to show count the number of timeseries of each node at the given level in current Metadata Tree. This could be used to query the number of sensors under each device. The grammar is: COUNT TIMESERIES <Path> GROUP BY LEVEL=<INTEGER>.

IoTDB > COUNT TIMESERIES root.**
IoTDB > COUNT TIMESERIES root.ln.**
IoTDB > COUNT TIMESERIES root.ln.*.*.status
IoTDB > COUNT TIMESERIES root.ln.wf01.wt01.status
IoTDB > COUNT TIMESERIES root.** WHERE TIMESERIES contains 'sgcc' 
IoTDB > COUNT TIMESERIES root.** WHERE DATATYPE = INT64
IoTDB > COUNT TIMESERIES root.** WHERE TAGS(unit) contains 'c' 
IoTDB > COUNT TIMESERIES root.** WHERE TAGS(unit) = 'c' 
IoTDB > COUNT TIMESERIES root.** WHERE TIMESERIES contains 'sgcc' group by level = 1

For example, if there are several timeseries (use show timeseries to show all timeseries):

+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
|                     timeseries|   alias|     database|dataType|encoding|compression|                                       tags|                                              attributes|deadband|deadband parameters|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
|root.sgcc.wf03.wt01.temperature|    null|    root.sgcc|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|    null|               null|
|     root.sgcc.wf03.wt01.status|    null|    root.sgcc| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|    null|               null|
|             root.turbine.d1.s1|newAlias| root.turbine|   FLOAT|     RLE|     SNAPPY|{"newTag1":"newV1","tag4":"v4","tag3":"v3"}|{"attr2":"v2","attr1":"newV1","attr4":"v4","attr3":"v3"}|    null|               null|
|     root.ln.wf02.wt02.hardware|    null|      root.ln|    TEXT|   PLAIN|     SNAPPY|                               {"unit":"c"}|                                                    null|    null|               null|
|       root.ln.wf02.wt02.status|    null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|                    {"description":"test1"}|                                                    null|    null|               null|
|  root.ln.wf01.wt01.temperature|    null|      root.ln|   FLOAT|     RLE|     SNAPPY|                                       null|                                                    null|    null|               null|
|       root.ln.wf01.wt01.status|    null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|                                       null|                                                    null|    null|               null|
+-------------------------------+--------+-------------+--------+--------+-----------+-------------------------------------------+--------------------------------------------------------+--------+-------------------+
Total line number = 7
It costs 0.004s

Then the Metadata Tree will be as below:

As can be seen, root is considered as LEVEL=0. So when you enter statements such as:

IoTDB > COUNT TIMESERIES root.** GROUP BY LEVEL=1
IoTDB > COUNT TIMESERIES root.ln.** GROUP BY LEVEL=2
IoTDB > COUNT TIMESERIES root.ln.wf01.* GROUP BY LEVEL=2

You will get following results:

+------------+-----------------+
|      column|count(timeseries)|
+------------+-----------------+
|   root.sgcc|                2|
|root.turbine|                1|
|     root.ln|                4|
+------------+-----------------+
Total line number = 3
It costs 0.002s

+------------+-----------------+
|      column|count(timeseries)|
+------------+-----------------+
|root.ln.wf02|                2|
|root.ln.wf01|                2|
+------------+-----------------+
Total line number = 2
It costs 0.002s

+------------+-----------------+
|      column|count(timeseries)|
+------------+-----------------+
|root.ln.wf01|                2|
+------------+-----------------+
Total line number = 1
It costs 0.002s

Note: The path of timeseries is just a filter condition, which has no relationship with the definition of level.

Active Timeseries Query

By adding WHERE time filter conditions to the existing SHOW/COUNT TIMESERIES, we can obtain time series with data within the specified time range.

It is important to note that in metadata queries with time filters, views are not considered; only the time series actually stored in the TsFile are taken into account.

An example usage is as follows:

IoTDB> insert into root.sg.data(timestamp, s1,s2) values(15000, 1, 2);
IoTDB> insert into root.sg.data2(timestamp, s1,s2) values(15002, 1, 2);
IoTDB> insert into root.sg.data3(timestamp, s1,s2) values(16000, 1, 2);
IoTDB> show timeseries;
+----------------+-----+--------+--------+--------+-----------+----+----------+--------+------------------+--------+
|      Timeseries|Alias|Database|DataType|Encoding|Compression|Tags|Attributes|Deadband|DeadbandParameters|ViewType|
+----------------+-----+--------+--------+--------+-----------+----+----------+--------+------------------+--------+
| root.sg.data.s1| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
| root.sg.data.s2| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
|root.sg.data3.s1| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
|root.sg.data3.s2| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
|root.sg.data2.s1| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
|root.sg.data2.s2| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
+----------------+-----+--------+--------+--------+-----------+----+----------+--------+------------------+--------+

IoTDB> show timeseries where time >= 15000 and time < 16000;
+----------------+-----+--------+--------+--------+-----------+----+----------+--------+------------------+--------+
|      Timeseries|Alias|Database|DataType|Encoding|Compression|Tags|Attributes|Deadband|DeadbandParameters|ViewType|
+----------------+-----+--------+--------+--------+-----------+----+----------+--------+------------------+--------+
| root.sg.data.s1| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
| root.sg.data.s2| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
|root.sg.data2.s1| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
|root.sg.data2.s2| null| root.sg|   FLOAT| GORILLA|        LZ4|null|      null|    null|              null|    BASE|
+----------------+-----+--------+--------+--------+-----------+----+----------+--------+------------------+--------+

IoTDB> count timeseries where time >= 15000 and time < 16000;
+-----------------+
|count(timeseries)|
+-----------------+
|                4|
+-----------------+

Regarding the definition of active time series, data that can be queried normally is considered active, meaning time series that have been inserted but deleted are not included.

Tag and Attribute Management

We can also add an alias, extra tag and attribute information while creating one timeseries.

The differences between tag and attribute are:

Tag could be used to query the path of timeseries, we will maintain an inverted index in memory on the tag: Tag -> Timeseries
Attribute could only be queried by timeseries path : Timeseries -> Attribute

The SQL statements for creating timeseries with extra tag and attribute information are extended as follows:

create timeseries root.turbine.d1.s1(temprature) with datatype=FLOAT, encoding=RLE, compression=SNAPPY tags(tag1=v1, tag2=v2) attributes(attr1=v1, attr2=v2)

The temprature in the brackets is an alias for the sensor s1. So we can use temprature to replace s1 anywhere.

IoTDB also supports using AS function to set alias. The difference between the two is: the alias set by the AS function is used to replace the whole time series name, temporary and not bound with the time series; while the alias mentioned above is only used as the alias of the sensor, which is bound with it and can be used equivalent to the original sensor name.

Notice that the size of the extra tag and attribute information shouldn't exceed the tag_attribute_total_size.

We can update the tag information after creating it as following:

Rename the tag/attribute key

ALTER timeseries root.turbine.d1.s1 RENAME tag1 TO newTag1

Reset the tag/attribute value

ALTER timeseries root.turbine.d1.s1 SET newTag1=newV1, attr1=newV1

Delete the existing tag/attribute

ALTER timeseries root.turbine.d1.s1 DROP tag1, tag2

Add new tags

ALTER timeseries root.turbine.d1.s1 ADD TAGS tag3=v3, tag4=v4

Add new attributes

ALTER timeseries root.turbine.d1.s1 ADD ATTRIBUTES attr3=v3, attr4=v4

Upsert alias, tags and attributes

add alias or a new key-value if the alias or key doesn't exist, otherwise, update the old one with new value.

ALTER timeseries root.turbine.d1.s1 UPSERT ALIAS=newAlias TAGS(tag3=v3, tag4=v4) ATTRIBUTES(attr3=v3, attr4=v4)

Show timeseries using tags. Use TAGS(tagKey) to identify the tags used as filter key

SHOW TIMESERIES (<`PathPattern`>)? timeseriesWhereClause

returns all the timeseries information that satisfy the where condition and match the pathPattern. SQL statements are as follows:

ALTER timeseries root.ln.wf02.wt02.hardware ADD TAGS unit=c
ALTER timeseries root.ln.wf02.wt02.status ADD TAGS description=test1
show timeseries root.ln.** where TAGS(unit)='c'
show timeseries root.ln.** where TAGS(description) contains 'test1'

The results are shown below respectly:

+--------------------------+-----+-------------+--------+--------+-----------+------------+----------+--------+-------------------+
|                timeseries|alias|     database|dataType|encoding|compression|        tags|attributes|deadband|deadband parameters|
+--------------------------+-----+-------------+--------+--------+-----------+------------+----------+--------+-------------------+
|root.ln.wf02.wt02.hardware| null|      root.ln|    TEXT|   PLAIN|     SNAPPY|{"unit":"c"}|      null|    null|               null|
+--------------------------+-----+-------------+--------+--------+-----------+------------+----------+--------+-------------------+
Total line number = 1
It costs 0.005s

+------------------------+-----+-------------+--------+--------+-----------+-----------------------+----------+--------+-------------------+
|              timeseries|alias|     database|dataType|encoding|compression|                   tags|attributes|deadband|deadband parameters|
+------------------------+-----+-------------+--------+--------+-----------+-----------------------+----------+--------+-------------------+
|root.ln.wf02.wt02.status| null|      root.ln| BOOLEAN|   PLAIN|     SNAPPY|{"description":"test1"}|      null|    null|               null|
+------------------------+-----+-------------+--------+--------+-----------+-----------------------+----------+--------+-------------------+
Total line number = 1
It costs 0.004s

count timeseries using tags

COUNT TIMESERIES (<`PathPattern`>)? timeseriesWhereClause
COUNT TIMESERIES (<`PathPattern`>)? timeseriesWhereClause GROUP BY LEVEL=<INTEGER>

returns all the number of timeseries that satisfy the where condition and match the pathPattern. SQL statements are as follows:

count timeseries
count timeseries root.** where TAGS(unit)='c'
count timeseries root.** where TAGS(unit)='c' group by level = 2

The results are shown below respectly :

IoTDB> count timeseries
+-----------------+
|count(timeseries)|
+-----------------+
|                6|
+-----------------+
Total line number = 1
It costs 0.019s
IoTDB> count timeseries root.** where TAGS(unit)='c'
+-----------------+
|count(timeseries)|
+-----------------+
|                2|
+-----------------+
Total line number = 1
It costs 0.020s
IoTDB> count timeseries root.** where TAGS(unit)='c' group by level = 2
+--------------+-----------------+
|        column|count(timeseries)|
+--------------+-----------------+
|  root.ln.wf02|                2|
|  root.ln.wf01|                0|
|root.sgcc.wf03|                0|
+--------------+-----------------+
Total line number = 3
It costs 0.011s

Notice that, we only support one condition in the where clause. Either it's an equal filter or it is an contains filter. In both case, the property in the where condition must be a tag.

create aligned timeseries

create aligned timeseries root.sg1.d1(s1 INT32 tags(tag1=v1, tag2=v2) attributes(attr1=v1, attr2=v2), s2 DOUBLE tags(tag3=v3, tag4=v4) attributes(attr3=v3, attr4=v4))

The execution result is as follows:

IoTDB> show timeseries
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+--------+-------------------+
|    timeseries|alias|     database|dataType|encoding|compression|                     tags|                 attributes|deadband|deadband parameters|
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+--------+-------------------+
|root.sg1.d1.s1| null|     root.sg1|   INT32|     RLE|     SNAPPY|{"tag1":"v1","tag2":"v2"}|{"attr2":"v2","attr1":"v1"}|    null|               null|
|root.sg1.d1.s2| null|     root.sg1|  DOUBLE| GORILLA|     SNAPPY|{"tag4":"v4","tag3":"v3"}|{"attr4":"v4","attr3":"v3"}|    null|               null|
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+--------+-------------------+

Support query：

IoTDB> show timeseries where TAGS(tag1)='v1'
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+--------+-------------------+
|    timeseries|alias|     database|dataType|encoding|compression|                     tags|                 attributes|deadband|deadband parameters|
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+--------+-------------------+
|root.sg1.d1.s1| null|     root.sg1|   INT32|     RLE|     SNAPPY|{"tag1":"v1","tag2":"v2"}|{"attr2":"v2","attr1":"v1"}|    null|               null|
+--------------+-----+-------------+--------+--------+-----------+-------------------------+---------------------------+--------+-------------------+

The above operations are supported for timeseries tag, attribute updates, etc.

Node Management

Show Child Paths

SHOW CHILD PATHS pathPattern

Return all child paths and their node types of all the paths matching pathPattern.

node types: ROOT -> DB INTERNAL -> DATABASE -> INTERNAL -> DEVICE -> TIMESERIES

Example：

return the child paths of root.ln：show child paths root.ln

+------------+----------+
| child paths|node types|
+------------+----------+
|root.ln.wf01|  INTERNAL|
|root.ln.wf02|  INTERNAL|
+------------+----------+
Total line number = 2
It costs 0.002s

get all paths in form of root.xx.xx.xx：show child paths root.xx.xx

Show Child Nodes

SHOW CHILD NODES pathPattern

Return all child nodes of the pathPattern.

Example：

return the child nodes of root：show child nodes root

+------------+
| child nodes|
+------------+
|          ln|
+------------+

return the child nodes of root.ln：show child nodes root.ln

+------------+
| child nodes|
+------------+
|        wf01|
|        wf02|
+------------+

Count Nodes

IoTDB is able to use COUNT NODES <PathPattern> LEVEL=<INTEGER> to count the number of nodes at the given level in current Metadata Tree considering a given pattern. IoTDB will find paths that match the pattern and counts distinct nodes at the specified level among the matched paths. This could be used to query the number of devices with specified measurements. The usage are as follows:

IoTDB > COUNT NODES root.** LEVEL=2
IoTDB > COUNT NODES root.ln.** LEVEL=2
IoTDB > COUNT NODES root.ln.wf01.** LEVEL=3
IoTDB > COUNT NODES root.**.temperature LEVEL=3

As for the above mentioned example and Metadata tree, you can get following results:

+------------+
|count(nodes)|
+------------+
|           4|
+------------+
Total line number = 1
It costs 0.003s

+------------+
|count(nodes)|
+------------+
|           2|
+------------+
Total line number = 1
It costs 0.002s

+------------+
|count(nodes)|
+------------+
|           1|
+------------+
Total line number = 1
It costs 0.002s

+------------+
|count(nodes)|
+------------+
|           2|
+------------+
Total line number = 1
It costs 0.002s

Note: The path of timeseries is just a filter condition, which has no relationship with the definition of level.

Show Devices

SHOW DEVICES pathPattern? (WITH DATABASE)? devicesWhereClause? limitClause?

Similar to Show Timeseries, IoTDB also supports two ways of viewing devices:

SHOW DEVICES statement presents all devices' information, which is equal to SHOW DEVICES root.**.
SHOW DEVICES <PathPattern> statement specifies the PathPattern and returns the devices information matching the pathPattern and under the given level.
WHERE condition supports DEVICE contains 'xxx' to do a fuzzy query based on the device name.

SQL statement is as follows:

IoTDB> show devices
IoTDB> show devices root.ln.**
IoTDB> show devices root.ln.** where device contains 't'

You can get results below:

+-------------------+---------+
|            devices|isAligned|
+-------------------+---------+
|  root.ln.wf01.wt01|    false|
|  root.ln.wf02.wt02|    false|
|root.sgcc.wf03.wt01|    false|
|    root.turbine.d1|    false|
+-------------------+---------+
Total line number = 4
It costs 0.002s

+-----------------+---------+
|          devices|isAligned|
+-----------------+---------+
|root.ln.wf01.wt01|    false|
|root.ln.wf02.wt02|    false|
+-----------------+---------+
Total line number = 2
It costs 0.001s

isAligned indicates whether the timeseries under the device are aligned.

To view devices' information with database, we can use SHOW DEVICES WITH DATABASE statement.

SHOW DEVICES WITH DATABASE statement presents all devices' information with their database.
SHOW DEVICES <PathPattern> WITH DATABASE statement specifies the PathPattern and returns the devices' information under the given level with their database information.

SQL statement is as follows:

IoTDB> show devices with database
IoTDB> show devices root.ln.** with database

You can get results below:

+-------------------+-------------+---------+
|            devices|     database|isAligned|
+-------------------+-------------+---------+
|  root.ln.wf01.wt01|      root.ln|    false|
|  root.ln.wf02.wt02|      root.ln|    false|
|root.sgcc.wf03.wt01|    root.sgcc|    false|
|    root.turbine.d1| root.turbine|    false|
+-------------------+-------------+---------+
Total line number = 4
It costs 0.003s

+-----------------+-------------+---------+
|          devices|     database|isAligned|
+-----------------+-------------+---------+
|root.ln.wf01.wt01|      root.ln|    false|
|root.ln.wf02.wt02|      root.ln|    false|
+-----------------+-------------+---------+
Total line number = 2
It costs 0.001s

Count Devices

COUNT DEVICES /

The above statement is used to count the number of devices. At the same time, it is allowed to specify PathPattern to count the number of devices matching the PathPattern.

SQL statement is as follows:

IoTDB> show devices
IoTDB> count devices
IoTDB> count devices root.ln.**

You can get results below:

+-------------------+---------+
|            devices|isAligned|
+-------------------+---------+
|root.sgcc.wf03.wt03|    false|
|    root.turbine.d1|    false|
|  root.ln.wf02.wt02|    false|
|  root.ln.wf01.wt01|    false|
+-------------------+---------+
Total line number = 4
It costs 0.024s

+--------------+
|count(devices)|
+--------------+
|             4|
+--------------+
Total line number = 1
It costs 0.004s

+--------------+
|count(devices)|
+--------------+
|             2|
+--------------+
Total line number = 1
It costs 0.004s

Active Device Query

Similar to active timeseries query, we can add time filter conditions to device viewing and statistics to query active devices that have data within a certain time range. The definition of active here is the same as for active time series. An example usage is as follows:

IoTDB> insert into root.sg.data(timestamp, s1,s2) values(15000, 1, 2);
IoTDB> insert into root.sg.data2(timestamp, s1,s2) values(15002, 1, 2);
IoTDB> insert into root.sg.data3(timestamp, s1,s2) values(16000, 1, 2);
IoTDB> show devices;
+-------------------+---------+
|            devices|isAligned|
+-------------------+---------+
|       root.sg.data|    false|
|      root.sg.data2|    false|
|      root.sg.data3|    false|
+-------------------+---------+

IoTDB> show devices where time >= 15000 and time < 16000;
+-------------------+---------+
|            devices|isAligned|
+-------------------+---------+
|       root.sg.data|    false|
|      root.sg.data2|    false|
+-------------------+---------+

IoTDB> count devices where time >= 15000 and time < 16000;
+--------------+
|count(devices)|
+--------------+
|             2|
+--------------+