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

Description

Updated on 2023-10-23 GMT+08:00

As described in Overview, EXPLAIN displays the execution plan, but will not actually run SQL statements. EXPLAIN ANALYZE and EXPLAIN PERFORMANCE both will actually run SQL statements and return the execution information. This section describes the execution plan and execution information in detail.

Execution Plans

The following SQL statement is used as an example:

1
SELECT * FROM t1, t2 WHERE t1.c1 = t2.c2;

Run the EXPLAIN command and the output is as follows:

Interpretation of the execution plan level (vertical):

  1. Layer 1: Seq Scan on t2

    The table scan operator scans the table t2 using Seq Scan. At this layer, data in the table t2 is read from a buffer or disk, and then transferred to the upper-layer node for calculation.

  2. Layer 2: Hash

    Hash operator. It is used to calculate the hash value of the operator transferred from the lower layer for subsequent hash join operations.

  3. Layer 3: Seq Scan on t1

    The table scan operator scans the table t1 using Seq Scan. At this layer, data in the table t1 is read from a buffer or disk, and then transferred to the upper-layer node for hash join calculation.

  4. Layer 4: Hash Join

    Join operator. It is used to join data in the t1 and t2 tables using the hash join method and output the result data.

Keywords in the execution plan:

  1. Table access modes
    • Seq Scan

      Scans all rows of the table in sequence.

    • Index Scan

      The optimizer uses a two-step plan: the child plan node visits an index to find the locations of rows matching the index condition, and then the upper plan node actually fetches those rows from the table itself. Fetching rows separately is much more expensive than reading them sequentially, but because not all pages of the table have to be visited, this is still cheaper than a sequential scan. The upper-layer planning node sorts index-identified rows based on their physical locations before reading them. This minimizes the independent capturing overhead.

      If there are separate indexes on multiple columns referenced in WHERE, the optimizer might choose to use an AND or OR combination of the indexes. However, this requires the visiting of both indexes, so it is not necessarily a win compared to using just one index and treating the other condition as a filter.

      The following index scans featured with different sorting mechanisms are involved:

      • Bitmap index scan

        Fetches data pages using a bitmap.

      • Index scan using index_name

        Fetches table rows in index order, which makes them even more expensive to read. However, there are so few rows that the extra cost of sorting the row locations is unnecessary. This plan type is used mainly for queries fetching just a single row and queries having an ORDER BY condition that matches the index order, because no extra sorting step is needed to satisfy ORDER BY.

  2. Table connection modes
    • Nested Loop

      A nested loop is used for queries that have a smaller data set connected. In a nested loop join, the foreign table drives the internal table and each row returned from the foreign table should have a matching row in the internal table. The returned result set of all queries should be less than 10,000. The table that returns a smaller subset will work as a foreign table, and indexes are recommended for connection columns of the internal table.

    • (Sonic) Hash Join

      A hash join is used for large tables. The optimizer uses a hash join, in which rows of one table are entered into an in-memory hash table, after which the other table is scanned and the hash table is probed for matches to each row. Sonic and non-Sonic hash joins differ in their hash table structures, which do not affect the execution result set.

    • Merge Join

      In most cases, the execution performance of a merge join is lower than that of a hash join. However, if the source data has been pre-sorted and no more sorting is needed during the merge join, its performance excels.

  3. Operators
    • sort

      Sorts the result set.

    • filter

      The EXPLAIN output shows the WHERE clause being applied as a Filter condition attached to the Seq Scan plan node. This means that the plan node checks the condition for each row it scans, and returns only the ones that meet the condition. The estimated number of output rows has been reduced because of the WHERE clause. However, the scan will still have to visit all 10,000 rows, as a result, the cost is not decreased. It increases a bit (by 10,000 x cpu_operator_cost) to reflect the extra CPU time spent on checking the WHERE condition.

    • LIMIT

      Limits the number of output execution results. If a LIMIT condition is added, not all rows are retrieved.

Execution Information

The following SQL statement is used as an example:

select sum(t2.c1) from t1,t2 where t1.c1=t2.c2 group by t1.c2;

The output of running EXPLAIN PERFORMANCE is as follows:

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