MySQL 8 for Big Data
Effective data processing with MySQL 8, Hadoop, NoSQL APIs, and other Big Data tools
1st Edition
Published on 8. July 2025
296 pages
978-1-78839-042-2 (ISBN)
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Persons
Lakhatariya Jaydip :
Jaydip Lakhatariya has rich experience in portal and J2EE frameworks. He adapts quickly to any new technology and has a keen desire for constant improvement. Currently, Jaydip is associated with a leading open source enterprise development company, KNOWARTH Technologies, where he is engaged in various enterprise projects. Jaydip, a full-stack developer, has proven his versatility by adopting technologies such as Liferay, Java, Spring, Struts, Hadoop, MySQL, Elasticsearch, Cassandra, MongoDB, Jenkins, SCM, PostgreSQL, and many more. He has been recognized with awards such as Merit, Commitment to Service, and also as a Star Performer. He loves mentoring people and has been delivering training for Portals and J2EE frameworks.Mehta Chintan :
Chintan Mehta is a co-founder of KNOWARTH Technologies and heads the cloud/RIMS/DevOps team. He has rich, progressive experience in server administration of Linux, AWS Cloud, DevOps, RIMS, and on open source technologies. He is also an AWS Certified Solutions Architect. Chintan has authored MySQL 8 for Big Data, Mastering Apache Solr 7.x, MySQL 8 Administrator's Guide, and Hadoop Backup and Recovery Solutions. Also, he has reviewed Liferay Portal Performance Best Practices and Building Serverless Web Applications.Challawala Shabbir :
Shabbir Challawala has over 8 years of rich experience in providing solutions based on MySQL and PHP technologies. He is currently working with KNOWARTH Technologies. He has worked in various PHP-based e-commerce solutions and learning portals for enterprises. He has worked on different PHP-based frameworks, such as Magento E-commerce, Drupal CMS, and Laravel. Shabbir has been involved in various enterprise solutions at different phases, such as architecture design, database optimization, and performance tuning. He has been carrying good exposure of Software Development Life Cycle process thoroughly. He has worked on integrating Big Data technologies such as MongoDB and Elasticsearch with a PHP-based framework.Patel Kandarp :
Kandarp Patel leads PHP practices at KNOWARTH Technologies. He has vast experience in providing end-to-end solutions in CMS, LMS, WCM, and e-commerce, along with various integrations for enterprise customers. He has over 9 years of rich experience in providing solutions in MySQL, MongoDB, and PHP-based frameworks. Kandarp is also a certified MongoDB and Magento developer. Kandarp has experience in various Enterprise Application development phases of the Software Development Life Cycle and has played prominent role in requirement gathering, architecture design, database design, application development, performance tuning, and CD/CI. Kandarp has a Bachelor of Engineering in Information Technology from a reputed university in India.
Jaydip Lakhatariya has rich experience in portal and J2EE frameworks. He adapts quickly to any new technology and has a keen desire for constant improvement. Currently, Jaydip is associated with a leading open source enterprise development company, KNOWARTH Technologies, where he is engaged in various enterprise projects. Jaydip, a full-stack developer, has proven his versatility by adopting technologies such as Liferay, Java, Spring, Struts, Hadoop, MySQL, Elasticsearch, Cassandra, MongoDB, Jenkins, SCM, PostgreSQL, and many more. He has been recognized with awards such as Merit, Commitment to Service, and also as a Star Performer. He loves mentoring people and has been delivering training for Portals and J2EE frameworks.Mehta Chintan :
Chintan Mehta is a co-founder of KNOWARTH Technologies and heads the cloud/RIMS/DevOps team. He has rich, progressive experience in server administration of Linux, AWS Cloud, DevOps, RIMS, and on open source technologies. He is also an AWS Certified Solutions Architect. Chintan has authored MySQL 8 for Big Data, Mastering Apache Solr 7.x, MySQL 8 Administrator's Guide, and Hadoop Backup and Recovery Solutions. Also, he has reviewed Liferay Portal Performance Best Practices and Building Serverless Web Applications.Challawala Shabbir :
Shabbir Challawala has over 8 years of rich experience in providing solutions based on MySQL and PHP technologies. He is currently working with KNOWARTH Technologies. He has worked in various PHP-based e-commerce solutions and learning portals for enterprises. He has worked on different PHP-based frameworks, such as Magento E-commerce, Drupal CMS, and Laravel. Shabbir has been involved in various enterprise solutions at different phases, such as architecture design, database optimization, and performance tuning. He has been carrying good exposure of Software Development Life Cycle process thoroughly. He has worked on integrating Big Data technologies such as MongoDB and Elasticsearch with a PHP-based framework.Patel Kandarp :
Kandarp Patel leads PHP practices at KNOWARTH Technologies. He has vast experience in providing end-to-end solutions in CMS, LMS, WCM, and e-commerce, along with various integrations for enterprise customers. He has over 9 years of rich experience in providing solutions in MySQL, MongoDB, and PHP-based frameworks. Kandarp is also a certified MongoDB and Magento developer. Kandarp has experience in various Enterprise Application development phases of the Software Development Life Cycle and has played prominent role in requirement gathering, architecture design, database design, application development, performance tuning, and CD/CI. Kandarp has a Bachelor of Engineering in Information Technology from a reputed university in India.
Content
- Cover
- Copyright
- Credits
- About the Authors
- About the Reviewers
- www.PacktPub.com
- Customer Feedback
- Table of Contents
- Preface
- Chapter 1: Introduction to Big Data and MySQL 8
- The importance of Big Data
- Social media
- Politics
- Science and research
- Power and energy
- Fraud detection
- Healthcare
- Business mapping
- The life cycle of Big Data
- Volume
- Variety
- Velocity
- Veracity
- Phases of the Big Data life cycle
- Collect
- Store
- Analyze
- Governance
- Structured databases
- Basics of MySQL
- MySQL as a relational database management system
- Licensing
- Reliability and scalability
- Platform compatibility
- Releases
- New features in MySQL 8
- Transactional data dictionary
- Roles
- InnoDB auto increment
- Supporting invisible indexes
- Improving descending indexes
- SET PERSIST
- Expanded GIS support
- The default character set
- Extended bit-wise operations
- InnoDB Memcached
- NOWAIT and SKIP LOCKED
- Benefits of using MySQL
- Security
- Scalability
- An open source relational database management system
- High performance
- High availability
- Cross-platform capabilities
- Installing MySQL 8
- Obtaining MySQL 8
- MySQL 8 installation
- MySQL service commands
- Evolution of MySQL for Big Data
- Acquiring data in MySQL
- Organizing data in Hadoop
- Analyzing data
- Results of analysis
- Summary
- Chapter 2: Data Query Techniques in MySQL 8
- Overview of SQL
- Database storage engines and types
- InnoDB
- Important notes about InnoDB
- MyISAM
- Important notes about MyISAM tables
- Memory
- Archive
- Blackhole
- CSV
- Merge
- Federated
- NDB cluster
- Select statement in MySQL 8
- WHERE clause
- Equal To and Not Equal To
- Greater than and Less than
- LIKE
- IN/NOT IN
- BETWEEN
- ORDER BY clause
- LIMIT clause
- SQL JOINS
- INNER JOIN
- LEFT JOIN
- RIGHT JOIN
- CROSS JOIN
- UNION
- Subquery
- Optimizing SELECT statements
- Insert, replace, and update statements in MySQL 8
- Insert
- Update
- Replace
- Transactions in MySQL 8
- Aggregating data in MySQL 8
- The importance of aggregate functions
- GROUP BY clause
- HAVING clause
- Minimum
- Maximum
- Average
- Count
- Sum
- JSON
- JSON_OBJECTAGG
- JSON_ARRAYAGG
- Summary
- Chapter 3: Indexing your data for High-Performing Queries
- MySQL indexing
- Index structures
- Bitmap indexes
- Sparse indexes
- Dense indexes
- B-Tree indexes
- Hash indexes
- Creating or dropping indexes
- UNIQUE | FULLTEXT | SPATIAL
- Index_col_name
- Index_options
- KEY_BLOCK_SIZE
- With Parser
- COMMENT
- VISIBILITY
- index_type
- algorithm_option
- lock_option
- When to avoid indexing
- MySQL 8 index types
- Defining a primary index
- Primary indexes
- Natural keys versus surrogate keys
- Unique keys
- Defining a column index
- Composite indexes in MySQL 8
- Covering index
- Invisible indexes
- Descending indexes
- Defining a foreign key in the MySQL table
- RESTRICT
- CASCADE
- SET NULL
- NO ACTION
- SET DEFAULT
- Dropping foreign keys
- Full-text indexing
- Natural language fulltext search on InnoDB and MyISAM
- Fulltext indexing on InnoDB
- Fulltext search in Boolean mode
- Differentiating full-text indexing and like queries
- Spatial indexes
- Indexing JSON data
- Generated columns
- Virtual generated columns
- Stored generated columns
- Defining indexes on JSON
- Summary
- Chapter 4: Using Memcached with MySQL 8
- Overview of Memcached
- Setting up Memcached
- Installation
- Verification
- Using of Memcached
- Performance tuner
- Caching tool
- Easy to use
- Analyzing data stored in Memcached
- Memcached replication configuration
- Memcached APIs for different technologies
- Memcached with Java
- Memcached with PHP
- Memcached with Ruby
- Memcached with Python
- Summary
- Chapter 5: Partitioning High Volume Data
- Partitioning in MySQL 8
- What is partitioning?
- Partitioning types
- Horizontal partitioning
- Vertical partitioning
- Horizontal partitioning in MySQL 8
- Range partitioning
- List partitioning
- Hash partitioning
- Column partitioning
- Range column partitioning
- List column partitioning
- Key partitioning
- Sub partitioning
- Vertical partitioning
- Splitting data into multiple tables
- Data normalization
- First normal form
- Second normal form
- Third normal form
- Boyce-Codd normal form
- Fourth normal form
- Fifth normal form
- Pruning partitions in MySQL
- Pruning with list partitioning
- Pruning with key partitioning
- Querying on partitioned data
- DELETE query with the partition option
- UPDATE query with the partition option
- INSERT query with the partition option
- Summary
- Chapter 6: Replication for building highly available solutions
- High availability
- MySQL replication
- MySQL cluster
- Oracle MySQL cloud service
- MySQL with the Solaris cluster
- Replication with MySQL
- Benefits of replication in MySQL 8
- Scalable applications
- Secure architecture
- Large data analysis
- Geographical data sharing
- Methods of replication in MySQL 8
- Replication using binary logs
- Replication using global transaction identifiers
- Replication configuration
- Replication with binary log file
- Replication master configuration
- Replication slave configuration
- Replication with GTIDs
- Global transaction identifiers
- The gtid_executed table
- GTID master's side configurations
- GTID slave's side configurations
- MySQL multi-source replication
- Multi-source replication configuration
- Statement-based versus row-based replication
- Group replication
- Requirements for group replication
- Group replication configuration
- Group replication settings
- Choosing a single master or multi-master
- Host-specific configuration settings
- Configuring a Replication User and enabling the Group Replication Plugin
- Starting group replication
- Bootstrap node
- Summary
- Chapter 7: MySQL 8 Best Practices
- MySQL benchmarks and configurations
- Resource utilization
- Stretch your timelines of benchmarks
- Replicating production settings
- Consistency of throughput and latency
- Sysbench can do more
- Virtualization world
- Concurrency
- Hidden workloads
- Nerves of your query
- Benchmarks
- Best practices for MySQL queries
- Data types
- Not null
- Indexing
- Search fields index
- Data types and joins
- Compound index
- Shorten up primary keys
- Index everything
- Fetch all data
- Application does the job
- Existence of data
- Limit yourself
- Analyze slow queries
- Query cost
- Best practices for the Memcached configuration
- Resource allocation
- Operating system architecture
- Default configurations
- Max object size
- Backlog queue limit
- Large pages support
- Sensitive data
- Restrict exposure
- Failover
- Namespaces
- Caching mechanism
- Memcached general statistics
- Best practices for replication
- Throughput in group replication
- Infrastructure sizing
- Constant throughput
- Contradictory workloads
- Write scalability
- Summary
- Chapter 8: NoSQL API for Integrating with Big Data Solutions
- NoSQL overview
- Changing rapidly over time
- Scaling
- Less management
- Best for big data
- NoSQL versus SQL
- Implementing NoSQL APIs
- NoSQL with the Memcached API layer
- Prerequisites
- NoSQL API with Java
- NoSQL API with PHP
- NoSQL API with Python
- NoSQL API with Perl
- NDB Cluster API
- NDB API for NodeJS
- NDB API for Java
- NDB API with C++
- Summary
- Chapter 9: Case study: Part I - Apache Sqoop for exchanging data between MySQL and Hadoop
- Case study for log analysis
- Using MySQL 8 and Hadoop for analyzing log
- Apache Sqoop overview
- Integrating Apache Sqoop with MySQL and Hadoop
- Hadoop
- MapReduce
- Hadoop distributed file system
- YARN
- Setting up Hadoop on Linux
- Installing Apache Sqoop
- Configuring MySQL connector
- Importing unstructured data to Hadoop HDFS from MySQL
- Sqoop import for fetching data from MySQL 8
- Incremental imports using Sqoop
- Loading structured data to MySQL using Apache Sqoop
- Sqoop export for storing structured data from MySQL 8
- Sqoop saved jobs
- Summary
- Chapter 10: Case study: Part II - Real time event processing using MySQL applier
- Case study overview
- MySQL Applier
- SQL Dump and Import
- Sqoop
- Tungsten replicator
- Apache Kafka
- Talend
- Dell Shareplex
- Comparison of Tools
- MySQL Applier overview
- MySQL Applier installation
- libhdfs
- cmake
- gcc
- FindHDFS.cmake
- Hive
- Real-time integration with MySQL Applier
- Organizing and analyzing data in Hadoop
- Summary
- Index
