Table of Contents MySQL InnoDB storage engine uses B + tree for indexing instead of B tree Introduction to B-Tree and B+Tree Why Choose B+Tree Application scenarios of B + tree Summarize Sample code MySQL InnoDB storage engine uses B + tree for indexing instead of B tree MySQL is a commonly used relational database […]
Tag: indexing
[MySQL Indexing and Optimization] Database design practice (including ER model)
Database design practice (including ER model) Article directory Database design practice (including ER model) 1. ER model 1.1 Overview 1.2 Modeling analysis 1.3 Refinement of ER model 1.4 Convert ER model diagram into data table 1. Convert an entity into a database table 2. Convert a many-to-many relationship into a data table 3. Express a […]
[MySQL Indexing and Optimization] Use of database optimization and performance analysis tools
Using database optimization and performance analysis tools Article directory Use of database optimization and performance analysis tools 1. Steps for database server optimization 2. Query system performance parameters 3. Locate the SQL that is fully executed: slow query log 4. View SQL execution costs: show profile 5. Analysis query tool: explain 5.1id 5.2 type 6. […]
[MySQL Indexing and Optimization] InnoDB data storage structure
Article directory 1. Database storage structure: page 1.1 The basic unit of disk and memory interaction: page 1.2 Overview of page structure 1.3 Page Superstructure 2. Internal structure of the page 3. InnoDB row format (or record format) 3.1 Compact line format 3.2 Dynamic and Compressed row formats 3.3 Redundant row format 4. Area, segment […]
[MySQL Indexing and Optimization] Index data structure
Article directory 1 Overview 2. Common index structures 2.1 Clustered index 2.2 Secondary index (auxiliary index, non-clustered index) 2.3 Joint index 3. Things to note about InnoDB’s B+ tree index 3.1 The location of the root page remains unchanged for thousands of years. 3.2 Uniqueness of directory entry records in internal nodes 4. Index scheme […]
A brief discussion on Elasticsearch indexing and mapping mechanism
Elasticsearch index and mapping mechanism Elasticsearch is a distributed, real-time search and analysis engine suitable for scenarios such as full-text search, structured search and analysis. In order to achieve high-performance search and analysis functions, Elasticsearch uses a data structure called an index and defines the structure and processing of data through a mapping mechanism. This […]
oracle automatic indexing
Remark: Oracle’s automatic indexing can only be implemented on an all-in-one machine. It cannot be used if it is not an all-in-one machine and an error will be reported. SYS@test>EXEC DBMS_AUTO_INDEX.CONFIGURE(‘AUTO_INDEX_COMPRESSION’, ‘ON’); BEGIN DBMS_AUTO_INDEX.CONFIGURE(‘AUTO_INDEX_COMPRESSION’, ‘ON’); END; * ERROR at line 1: ORA-40216: feature not supported ORA-06512: at “SYS.DBMS_SYS_ERROR”, line 79 ORA-06512: at “SYS.DBMS_AUTO_INDEX_INTERNAL”, line 10888 […]
MySQL forces the use of two methods of indexing and optimizes the index, and uses MySQL stored procedures to create test data.
1. Two ways for MySQL to force the use of indexes 1. Use the FORCE INDEX statement: explain select * from tbl_test force index (index_item_code) where (item_code between 1 and 1000) and (random between 50000 and 1000000) order by random limit 1; Use FORCE INDEX (index name) to index: 2. Use the USE INDEX statement: […]
Numpy Data Analysis 02 – Slicing and Indexing
Slicing and indexing of Numpy arrays 1. Slicing and indexing of one-dimensional arrays Colon split slicing parameters [start:stop:step] The contents of an ndarray object can be accessed and modified by indexing or slicing, just like the slicing operation of lists in Python. ndarray arrays can be indexed based on subscripts from 0-n Note: The difference […]
Two: Shape and reshaping of Numpy arrays&& Three: Indexing and slicing of Numpy arrays (one-dimensional, two-dimensional, three-dimensional)&& Four: Stacking and cascading of Numpy arrays&& Five: Numpy array broadcast&& Six: Calculation with Numpy arrays
Two: Shape and reshaping of Numpy arrays Below are some inline code snippets. // A code block var foo = ‘bar’; // An highlighted block 2.1 View the dimensions of a NumPy array array.ndim input:a = np.array([[5,10,15],[20,25,20]]) print(‘Array :’,’\\ ‘,a) print(‘Dimensions :’,a.ndim) output:Array : [[ 5 10 15] [20 25 20]] Dimensions: 2 2.2 Check […]