Compute
Elastic Cloud Server
Huawei Cloud Flexus
Bare Metal Server
Auto Scaling
Image Management Service
Dedicated Host
FunctionGraph
Cloud Phone Host
Huawei Cloud EulerOS
Networking
Virtual Private Cloud
Elastic IP
Elastic Load Balance
NAT Gateway
Direct Connect
Virtual Private Network
VPC Endpoint
Cloud Connect
Enterprise Router
Enterprise Switch
Global Accelerator
Management & Governance
Cloud Eye
Identity and Access Management
Cloud Trace Service
Resource Formation Service
Tag Management Service
Log Tank Service
Config
OneAccess
Resource Access Manager
Simple Message Notification
Application Performance Management
Application Operations Management
Organizations
Optimization Advisor
IAM Identity Center
Cloud Operations Center
Resource Governance Center
Migration
Server Migration Service
Object Storage Migration Service
Cloud Data Migration
Migration Center
Cloud Ecosystem
KooGallery
Partner Center
User Support
My Account
Billing Center
Cost Center
Resource Center
Enterprise Management
Service Tickets
HUAWEI CLOUD (International) FAQs
ICP Filing
Support Plans
My Credentials
Customer Operation Capabilities
Partner Support Plans
Professional Services
Analytics
MapReduce Service
Data Lake Insight
CloudTable Service
Cloud Search Service
Data Lake Visualization
Data Ingestion Service
GaussDB(DWS)
DataArts Studio
Data Lake Factory
DataArts Lake Formation
IoT
IoT Device Access
Others
Product Pricing Details
System Permissions
Console Quick Start
Common FAQs
Instructions for Associating with a HUAWEI CLOUD Partner
Message Center
Security & Compliance
Security Technologies and Applications
Web Application Firewall
Host Security Service
Cloud Firewall
SecMaster
Anti-DDoS Service
Data Encryption Workshop
Database Security Service
Cloud Bastion Host
Data Security Center
Cloud Certificate Manager
Edge Security
Managed Threat Detection
Blockchain
Blockchain Service
Web3 Node Engine Service
Media Services
Media Processing Center
Video On Demand
Live
SparkRTC
MetaStudio
Storage
Object Storage Service
Elastic Volume Service
Cloud Backup and Recovery
Storage Disaster Recovery Service
Scalable File Service Turbo
Scalable File Service
Volume Backup Service
Cloud Server Backup Service
Data Express Service
Dedicated Distributed Storage Service
Containers
Cloud Container Engine
SoftWare Repository for Container
Application Service Mesh
Ubiquitous Cloud Native Service
Cloud Container Instance
Databases
Relational Database Service
Document Database Service
Data Admin Service
Data Replication Service
GeminiDB
GaussDB
Distributed Database Middleware
Database and Application Migration UGO
TaurusDB
Middleware
Distributed Cache Service
API Gateway
Distributed Message Service for Kafka
Distributed Message Service for RabbitMQ
Distributed Message Service for RocketMQ
Cloud Service Engine
Multi-Site High Availability Service
EventGrid
Dedicated Cloud
Dedicated Computing Cluster
Business Applications
Workspace
ROMA Connect
Message & SMS
Domain Name Service
Edge Data Center Management
Meeting
AI
Face Recognition Service
Graph Engine Service
Content Moderation
Image Recognition
Optical Character Recognition
ModelArts
ImageSearch
Conversational Bot Service
Speech Interaction Service
Huawei HiLens
Video Intelligent Analysis Service
Developer Tools
SDK Developer Guide
API Request Signing Guide
Terraform
Koo Command Line Interface
Content Delivery & Edge Computing
Content Delivery Network
Intelligent EdgeFabric
CloudPond
Intelligent EdgeCloud
Solutions
SAP Cloud
High Performance Computing
Developer Services
ServiceStage
CodeArts
CodeArts PerfTest
CodeArts Req
CodeArts Pipeline
CodeArts Build
CodeArts Deploy
CodeArts Artifact
CodeArts TestPlan
CodeArts Check
CodeArts Repo
Cloud Application Engine
MacroVerse aPaaS
KooMessage
KooPhone
KooDrive
On this page

Show all

Window Functions

Updated on 2024-05-07 GMT+08:00

Window Functions

This statement is used together with the window function. The OVER clause is used for grouping data and sorting the elements in a group. Window functions are used for generating sequence numbers for the values in the group.

NOTE:

ORDER BY in a window function must be followed by a column name. If it is followed by a number, the number is processed as a constant value and the target column is not ranked.

  • RANK()

    Description: The RANK function is used for generating non-consecutive sequence numbers for the values in each group. The same values have the same sequence number.

    Return type: bigint

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    gaussdb=# CREATE TABLE rank_t1(a int, b int);
    
    gaussdb=# INSERT INTO rank_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6);
    
    gaussdb=# SELECT a,b,RANK() OVER(PARTITION BY a ORDER BY b) FROM rank_t1;
     a | b | rank 
    ---+---+------
     1 | 1 |    1
     1 | 1 |    1
     1 | 2 |    3
     1 | 3 |    4
     2 | 4 |    1
     2 | 5 |    2
     3 | 6 |    1
    (7 rows)
    
    gaussdb=# DROP TABLE rank_t1;
    
  • ROW_NUMBER()

    Description: The ROW_NUMBER function is used for generating consecutive sequence numbers for the values in each group. The same values have different sequence numbers.

    Return type: bigint

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    gaussdb=# CREATE TABLE row_number_t1(a int, b int);
    
    gaussdb=# INSERT INTO row_number_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6);
    
    gaussdb=# SELECT a,b,ROW_NUMBER() OVER(PARTITION BY a ORDER BY b) FROM row_number_t1;
     a | b | row_number 
    ---+---+------------
     1 | 1 |          1
     1 | 1 |          2
     1 | 2 |          3
     1 | 3 |          4
     2 | 4 |          1
     2 | 5 |          2
     3 | 6 |          1
    (7 rows)
    
    gaussdb=# DROP TABLE row_number_t1;
    
  • DENSE_RANK()

    Description: The DENSE_RANK function is used for generating consecutive sequence numbers for the values in each group. The same values have the same sequence number.

    Return type: bigint

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    gaussdb=# CREATE TABLE dense_rank_t1(a int, b int);
    
    gaussdb=# INSERT INTO dense_rank_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6);
    
    gaussdb=# SELECT a,b,DENSE_RANK() OVER(PARTITION BY a ORDER BY b) FROM dense_rank_t1;
     a | b | dense_rank 
    ---+---+------------
     1 | 1 |          1
     1 | 1 |          1
     1 | 2 |          2
     1 | 3 |          3
     2 | 4 |          1
     2 | 5 |          2
     3 | 6 |          1
    (7 rows)
    
    gaussdb=# DROP TABLE dense_rank_t1;
    
  • PERCENT_RANK()

    Description: The PERCENT_RANK function is used for generating corresponding sequence numbers for the values in each group. That is, the function calculates the value according to the formula: Sequence number = (rank - 1) / (totalrows - 1). rank is the corresponding sequence number generated based on the RANK function for the value and totalrows is the total number of elements in a group.

    Return type: double precision

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    gaussdb=# CREATE TABLE percent_rank_t1(a int, b int);
    
    gaussdb=# INSERT INTO percent_rank_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6);
    
    gaussdb=# SELECT a,b,PERCENT_RANK() OVER(PARTITION BY a ORDER BY b) FROM percent_rank_t1;
     a | b |   percent_rank   
    ---+---+------------------
     1 | 1 |                0
     1 | 1 |                0
     1 | 2 | .666666666666667
     1 | 3 |                1
     2 | 4 |                0
     2 | 5 |                1
     3 | 6 |                0
    (7 rows)
    
    gaussdb=# DROP TABLE percent_rank_t1;
    
  • CUME_DIST()

    Description: The CUME_DIST function is used for generating accumulative distribution sequence numbers for the values in each group. That is, the function calculates the value according to the following formula: Sequence number = Number of rows preceding or peer with current row/Total rows.

    Return type: double precision

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    gaussdb=# CREATE TABLE cume_dist_t1(a int, b int);
    
    gaussdb=# INSERT INTO cume_dist_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6);
    
    gaussdb=# SELECT a,b,CUME_DIST() OVER(PARTITION BY a ORDER BY b) FROM cume_dist_t1;
     a | b | cume_dist 
    ---+---+-----------
     1 | 1 |        .5
     1 | 1 |        .5
     1 | 2 |       .75
     1 | 3 |         1
     2 | 4 |        .5
     2 | 5 |         1
     3 | 6 |         1
    (7 rows)
    
    gaussdb=# DROP TABLE cume_dist_t1;
    
  • NTILE(num_buckets integer)

    Description: The NTILE function is used for equally allocating sequential data sets to the buckets whose quantity is specified by num_buckets according to num_buckets integer and allocating the bucket number to each row. Divide the partition as evenly as possible.

    Return type: integer

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    gaussdb=# CREATE TABLE ntile_t1(a int, b int);
    
    gaussdb=# INSERT INTO ntile_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6);
    
    gaussdb=# SELECT a,b,NTILE(2) OVER(PARTITION BY a ORDER BY b) FROM ntile_t1;
     a | b | ntile 
    ---+---+-------
     1 | 1 |     1
     1 | 1 |     1
     1 | 2 |     2
     1 | 3 |     2
     2 | 4 |     1
     2 | 5 |     2
     3 | 6 |     1
    (7 rows)
    
    gaussdb=# DROP TABLE ntile_t1;
    
  • LAG(value any [, offset integer [, default any ]])

    Description: The LAG function is used for generating lag values for the corresponding values in each group. That is, the value of the row obtained by moving forward the row corresponding to the current value by offset (integer) is the sequence number. If the row does not exist after the moving, the result value is the default value. If omitted, offset defaults to 1 and default to NULL. The type of the default value must be the same as that of the value value.

    Return type: same as the parameter type

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    18
    19
    20
    21
    22
    23
    24
    25
    26
    27
    28
    29
    30
    31
    32
    33
    34
    35
    36
    37
    38
    39
    40
    41
    42
    43
    44
    45
    46
    47
    48
    -- Create a table and insert data into the table.
    gaussdb=# CREATE TABLE ta1 (hire_date date, last_name varchar(20), department_id int);
    CREATE TABLE
    gaussdb=# INSERT INTO ta1 VALUES('07-DEC-02', 'Raphaely', 30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 VALUES('24-JUL-05', 'Tobias',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 VALUES('24-DEC-05', 'Baida',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 VALUES('18-MAY-03', 'Khoo', 30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('15-NOV-06', 'Himuro',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('10-AUG-07', 'Colmenares',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('10-MAY-07', 'yq',  11);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('10-MAY-08', 'zi',  11);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('', 'yq1',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values(null, 'yq2',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('10-DEC-07', 'yq3',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values(null, null,  11);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values(null, null,  11);
    INSERT 0 1
    
    -- Call LAG and set offset to 3 and default to null.
    gaussdb=# SELECT hire_date, last_name, department_id, lag(hire_date, 3, null)  OVER (PARTITION BY department_id ORDER BY last_name) AS "NextHired" FROM ta1 ORDER BY department_id;
          hire_date      | last_name  | department_id |      NextHired
    ---------------------+------------+---------------+---------------------
     2007-05-10 00:00:00 | yq         |            11 |
     2008-05-10 00:00:00 | zi         |            11 |
                         |            |            11 |
                         |            |            11 | 2007-05-10 00:00:00
     2005-12-24 00:00:00 | Baida      |            30 |
     2007-08-10 00:00:00 | Colmenares |            30 |
     2006-11-15 00:00:00 | Himuro     |            30 |
     2003-05-18 00:00:00 | Khoo       |            30 | 2005-12-24 00:00:00
     2002-12-07 00:00:00 | Raphaely   |            30 | 2007-08-10 00:00:00
     2005-07-24 00:00:00 | Tobias     |            30 | 2006-11-15 00:00:00
                         | yq1        |            30 | 2003-05-18 00:00:00
                         | yq2        |            30 | 2002-12-07 00:00:00
     2007-12-10 00:00:00 | yq3        |            30 | 2005-07-24 00:00:00
    (13 rows)
    
  • LEAD(value any [, offset integer [, default any ]])

    Description: The LEAD function is used for generating leading values for the corresponding values in each group. That is, the value of the row obtained by moving backward the row corresponding to the current value by offset (integer) is the sequence number. If the row after the moving exceeds the total number of rows for the current group, the result value is the default value. If omitted, offset defaults to 1 and default to NULL. The type of the default value must be the same as that of the value value.

    Return type: same as the parameter type

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    18
    19
    20
    21
    22
    23
    24
    25
    26
    27
    28
    29
    30
    31
    32
    33
    34
    35
    36
    37
    38
    39
    40
    41
    42
    43
    44
    45
    46
    47
    48
    -- Create a table and insert data into the table.
    gaussdb=# CREATE TABLE ta1 (hire_date date, last_name varchar(20), department_id int);
    CREATE TABLE
    gaussdb=# INSERT INTO ta1 values('07-DEC-02', 'Raphaely', 30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('24-JUL-05', 'Tobias',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('24-DEC-05', 'Baida',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('18-MAY-03', 'Khoo', 30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('15-NOV-06', 'Himuro',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('10-AUG-07', 'Colmenares',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('10-MAY-07', 'yq',  11);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('10-MAY-08', 'zi',  11);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('', 'yq1',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values(null, 'yq2',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values('10-DEC-07', 'yq3',  30);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values(null, null,  11);
    INSERT 0 1
    gaussdb=# INSERT INTO ta1 values(null, null,  11);
    INSERT 0 1
    
    -- Call LEAD and set offset to 2.
    gaussdb=# SELECT hire_date, last_name, department_id, lead(hire_date, 2) OVER (PARTITION BY department_id ORDER BY last_name) AS "NextHired" FROM ta1 ORDER BY department_id;
          hire_date      | last_name  | department_id |      NextHired
    ---------------------+------------+---------------+---------------------
     2007-05-10 00:00:00 | yq         |            11 |
     2008-05-10 00:00:00 | zi         |            11 |
                         |            |            11 |
                         |            |            11 |
     2005-12-24 00:00:00 | Baida      |            30 | 2006-11-15 00:00:00
     2007-08-10 00:00:00 | Colmenares |            30 | 2003-05-18 00:00:00
     2006-11-15 00:00:00 | Himuro     |            30 | 2002-12-07 00:00:00
     2003-05-18 00:00:00 | Khoo       |            30 | 2005-07-24 00:00:00
     2002-12-07 00:00:00 | Raphaely   |            30 |
     2005-07-24 00:00:00 | Tobias     |            30 |
                         | yq1        |            30 | 2007-12-10 00:00:00
                         | yq2        |            30 |
     2007-12-10 00:00:00 | yq3        |            30 |
    (13 rows)
    
  • FIRST_VALUE(value any)

    Description: Returns the first value of each group.

    Return type: same as the parameter type

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    gaussdb=# CREATE TABLE first_value_t1(a int, b int);
    
    gaussdb=# INSERT INTO first_value_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6);
    
    gaussdb=# SELECT a,b,FIRST_VALUE(b) OVER(PARTITION BY a ORDER BY b) FROM first_value_t1;
     a | b | first_value 
    ---+---+-------------
     1 | 1 |           1
     1 | 1 |           1
     1 | 2 |           1
     1 | 3 |           1
     2 | 4 |           4
     2 | 5 |           4
     3 | 6 |           6
    (7 rows)
    
    gaussdb=# DROP TABLE first_value_t1;
    
  • LAST_VALUE(value any)

    Description: Returns the last value of each group.

    Return type: same as the parameter type

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    gaussdb=# CREATE TABLE last_value_t1(a int, b int);
    
    gaussdb=# INSERT INTO last_value_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6);
    
    gaussdb=# SELECT a,b,LAST_VALUE(b) OVER(PARTITION BY a ORDER BY b) FROM last_value_t1;
     a | b | last_value 
    ---+---+------------
     1 | 1 |          1
     1 | 1 |          1
     1 | 2 |          2
     1 | 3 |          3
     2 | 4 |          4
     2 | 5 |          5
     3 | 6 |          6
    (7 rows)
    
    gaussdb=# DROP TABLE last_value_t1;
    
  • NTH_VALUE(value any, nth integer)

    Description: The nth row for a group is the returned value. If the row does not exist, NULL is returned by default.

    Return type: same as the parameter type

    Example:

     1
     2
     3
     4
     5
     6
     7
     8
     9
    10
    11
    12
    13
    14
    15
    16
    17
    gaussdb=# CREATE TABLE nth_value_t1(a int, b int);
    
    gaussdb=# INSERT INTO nth_value_t1 VALUES(1,1),(1,1),(1, 2),(1, 3),(2, 4),(2, 5),(3,6);
    
    gaussdb=# SELECT a,b,NTH_VALUE(b, 2) OVER(PARTITION BY a order by b) FROM nth_value_t1;
     a | b | nth_value 
    ---+---+-----------
     1 | 1 |         1
     1 | 1 |         1
     1 | 2 |         1
     1 | 3 |         1
     2 | 4 |          
     2 | 5 |         5
     3 | 6 |          
    (7 rows)
    
    gaussdb=# DROP TABLE nth_value_t1;
    
  • delta

    Description: Returns the difference between the current row and the previous row.

    Parameter: numeric

    Return type: numeric

  • spread

    Description: Calculates the difference between the maximum value and minimum value in a certain period.

    Parameter: real

    Return type: real

We use cookies to improve our site and your experience. By continuing to browse our site you accept our cookie policy. Find out more

Feedback

Feedback

Feedback

0/500

Selected Content

Submit selected content with the feedback