1.1
Table Of Contents
- Contents
- About the SQLFire User's Guide
- Supported Configurations and System Requirements
- Getting Started with vFabric SQLFire
- Managing Your Data in vFabric SQLFire
- Designing vFabric SQLFire Databases
- Using Server Groups to Manage Data
- Partitioning Tables
- Replicating Tables
- Estimating Memory Requirements
- Using Disk Stores to Persist Data
- Exporting and Importing Data with vFabric SQLFire
- Using Table Functions to Import Data as a SQLFire Tables
- Developing Applications with SQLFire
- Starting SQLFire Servers with the FabricServer Interface
- Developing Java Clients and Peers
- Configuring SQLFire as a JDBC Datasource
- Storing and Loading JAR Files in SQLFire
- Developing ADO.NET Client Applications
- About the ADO.NET Driver
- ADO.NET Driver Classes
- Installing and Using the ADO.NET driver
- Connecting to SQLFire with the ADO.NET Driver
- Managing Connections
- Executing SQL Commands
- Working with Result Sets
- Storing a Table
- Storing Multiple Tables
- Specifying Command Parameters with SQLFParameter
- Updating Row Data
- Adding Rows to a Table
- Managing SQLFire Transactions
- Performing Batch Updates
- Generic Coding with the SQLFire ADO.NET Driver
- Using SQLFire.NET Designer
- Understanding the Data Consistency Model
- Using Distributed Transactions in Your Applications
- Using Data-Aware Stored Procedures
- Using the Procedure Provider API
- Using the Custom Result Processor API
- Programming User-Defined Types
- Using Result Sets and Cursors
- Caching Data with vFabric SQLFire
- Deploying vFabric SQLFire
- SQLFire Deployment Models
- Steps to Plan and Configure a Deployment
- Configuring Discovery Mechanisms
- Starting and Configuring SQLFire Servers
- Configuring Multi-site (WAN) Deployments
- Configuring Authentication and Authorization
- Configuring User Authentication
- User Names in Authentication and Authorization
- Configuring User Authorization
- Configuring Network Encryption and Authentication with SSL/TLS
- Managing and Monitoring vFabric SQLFire
- Configuring and Using SQLFire Log Files
- Querying SQLFire System Tables and Indexes
- Evaluating Query Plans and Query Statistics
- Overriding Optimizer Choices
- Evaluating System and Application Performance
- Using Java Management Extensions (JMX)
- Best Practices for Tuning Performance
- Detecting and Handling Network Segmentation ("Split Brain")
- vFabric SQLFire Reference
- Configuration Properties
- JDBC API
- Mapping java.sql.Types to SQL Types
- java.sql.BatchUpdateException Class
- java.sql.Connection Interface
- java.sql.DatabaseMetaData Interface
- java.sql.Driver Interface
- java.sql.DriverManager.getConnection Method
- java.sql.PreparedStatement Interface
- java.sql.ResultSet Interface
- java.sql.SavePoint Class
- java.sql.SQLException Class
- java.sql.Statement Class
- javax.sql.XADataSource
- sqlf Launcher Commands
- sqlf backup
- sqlf compact-all-disk-stores
- sqlf compact-disk-store
- sqlf encrypt-password
- sqlf install-jar
- sqlf list-missing-disk-stores
- sqlf locator
- sqlf Logging Support
- sqlf merge-logs
- sqlf remove-jar
- sqlf replace-jar
- sqlf revoke-missing-disk-store
- sqlf server
- sqlf show-disk-store-metadata
- sqlf shut-down-all
- sqlf stats
- sqlf upgrade-disk-store
- sqlf validate-disk-store
- sqlf version
- sqlf write-data-dtd-to-file
- sqlf write-data-to-db
- sqlf write-data-to-xml
- sqlf write-schema-to-db
- sqlf write-schema-to-sql
- sqlf write-schema-to-xml
- sqlf Interactive Commands
- absolute
- after last
- async
- autocommit
- before first
- close
- commit
- connect
- connect client
- connect peer
- describe
- disconnect
- driver
- elapsedtime
- execute
- exit
- first
- get scroll insensitive cursor
- GetCurrentRowNumber
- help
- last
- LocalizedDisplay
- MaximumDisplayWidth
- next
- prepare
- previous
- protocol
- relative
- remove
- rollback
- run
- set connection
- show
- wait for
- SQLFire API
- SQL Language Reference
- Keywords and Identifiers
- SQL Statements
- ALTER TABLE
- CALL
- CREATE Statements
- DECLARE GLOBAL TEMPORARY TABLE
- DELETE
- EXPLAIN
- DROP statements
- GRANT
- INSERT
- REVOKE
- SELECT
- SET ISOLATION
- SET SCHEMA
- TRUNCATE TABLE
- UPDATE
- SQL Queries
- SQL Clauses
- SQL Expressions
- JOIN Operations
- Built-in Functions
- Standard Built-in Functions
- Aggregates (set functions)
- ABS or ABSVAL function
- ACOS function
- ASIN function
- ATAN function
- ATAN2 function
- AVG function
- BIGINT function
- CASE expressions
- CAST function
- CEIL or CEILING function
- CHAR function
- COALESCE function
- Concatenation operator
- COS function
- COSH function
- COT function
- COUNT function
- COUNT(*) function
- CURRENT DATE function
- CURRENT_DATE function
- CURRENT ISOLATION function
- CURRENT_ROLE function
- CURRENT SCHEMA function
- CURRENT TIME function
- CURRENT_TIME function
- CURRENT TIMESTAMP function
- CURRENT_TIMESTAMP function
- CURRENT_USER function
- DATE function
- DAY function
- DEGREES function
- DOUBLE function
- EXP function
- FLOOR function
- HOUR function
- INTEGER function
- LCASE or LOWER function
- LENGTH function
- LN or LOG function
- LOG10 function
- LOCATE function
- LTRIM function
- MAX function
- MIN function
- MINUTE function
- MOD function
- MONTH function
- NULLIF expressions
- PI function
- RADIANS function
- RANDOM function
- RAND function
- RTRIM function
- SECOND function
- SESSION_USER function
- SIGN function
- SIN function
- SINH function
- SMALLINT function
- SQRT function
- SUBSTR function
- SUM function
- TAN function
- TANH function
- TIME function
- TIMESTAMP function
- TRIM function
- UCASE or UPPER function
- USER function
- VARCHAR function
- XMLEXISTS operator
- XMLPARSE operator
- XMLQUERY operator
- XMLSERIALIZE operator
- YEAR function
- SQLFire Built-in Functions
- Standard Built-in Functions
- Built-in System Procedures
- Standard Built-in Procedures
- SYSCS_UTIL.EMPTY_STATEMENT_CACHE
- SYSCS_UTIL.EXPORT_QUERY
- SYSCS_UTIL.EXPORT_TABLE
- SYSCS_UTIL.IMPORT_DATA
- SYSCS_UTIL.IMPORT_DATA_EX
- SYSCS_UTIL.IMPORT_DATA_LOBS_FROM_EXTFILE system procedure
- SYSCS_UTIL.IMPORT_TABLE
- SYSCS_UTIL.IMPORT_TABLE_EX
- SYSCS_UTIL.IMPORT_TABLE_LOBS_FROM_EXTFILE
- SYSCS_UTIL.SET_EXPLAIN_CONNECTION
- SYSCS_UTIL.SET_STATISTICS_TIMING
- JAR Installation Procedures
- Callback Configuration Procedures
- Heap Eviction Configuration Procedures
- WAN Configuration Procedures
- Standard Built-in Procedures
- Data Types
- SQL Standards Conformance
- System Tables
- ASYNCEVENTLISTENERS
- GATEWAYRECEIVERS
- GATEWAYSENDERS
- INDEXES
- JARS
- MEMBERS
- MEMORYANALYTICS
- STATEMENTPLANS
- SYSALIASES
- SYSCHECKS
- SYSCOLPERMS
- SYSCOLUMNS
- SYSCONGLOMERATES
- SYSCONSTRAINTS
- SYSDEPENDS
- SYSDISKSTORES
- SYSFILES
- SYSFOREIGNKEYS
- SYSKEYS
- SYSROLES
- SYSROUTINEPERMS
- SYSSCHEMAS
- SYSSTATEMENTS
- SYSSTATISTICS
- SYSTABLEPERMS
- SYSTABLES
- SYSTRIGGERS
- SYSVIEWS
- Exception Messages and SQL States
- ADO.NET Driver Reference
- SQLFire Data Types in ADO.NET
- VMware.Data.SQLFire.BatchUpdateException
- VMWare.Data.SQLFire.SQLFClientConnection
- VMware.Data.SQLFire.SQLFCommand
- VMware.Data.SQLFire.SQLFCommandBuilder
- VMware.Data.SQLFire.SQLFType
- VMware.Data.SQLFire.SQLFDataAdapter
- VMware.Data.SQLFire.SQLFDataReader
- VMware.Data.SQLFire.SQLFException
- VMware.Data.SQLFire.SQLFParameter
- VMware.Data.SQLFire.SQLFParameterCollection
- VMware.Data.SQLFire.SQLFTransaction
- vFabric SQLFire Limitations
- Troubleshooting Common Problems
- vFabric SQLFire Glossary
- Index
Chapter 8
vFabric SQLFire Features and Benefits
The sections that follow summarize main features. The SQLFire community site provides additional information about
the features and benefits of SQLFire and a comparison of SQLFire to other data management systems. See also the
SQLFire product page.
In-Memory Data Management with Optimized Disk Persistence
SQLFire enables applications to manage data entirely in memory by using partitioning and synchronous replication
to distribute the data across numerous SQLFire members. SQLFire also provides an optimized disk persistence
mechanism with a non-flushing algorithm to maintain high performance in applications that require stable, long-term
storage. Applications can also use SQLFire to actively cache table data from a traditional disk-based RDBMS.
Continuous Availability, Elastically Scaled, Low Latency
A flexible architecture enables SQLFire to pool memory and disk resources from hundreds of clustered members. This
clustered approach provides extremely high throughput, predictable latency, dynamic and linear scalability, and
continuous availability of data. By collocating application logic with data and executing application logic in parallel,
SQLFire substantially increases application throughput. It also transparently re-executes application logic if a server
fails.
Highly Adaptable to Existing Applications
SQLFire is implemented entirely in Java, and it can be embedded directly within a Java application. You can also
deploy SQLFire members as standalone servers that participate in a cluster. Java applications can connect to a SQLFire
cluster using the provided JDBC drivers. Microsoft .NET and Mono applications can connect using the provided
ADO.NET driver.
The use of JDBC, ADO.NET, and SQL means that many existing database applications can be easily adapted to use
a SQLFire cluster. SQLFire introduces several extensions to common SQL Data Definition Language (DDL) statements
to manage data partitioning, replication, synchronization with data sources, and other features. However, most common
queries and Data Manipulation Language (DML) statements are based on ANSI SQL-92, so experienced database
application developers can use their knowledge of SQL when working with SQLFire.
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