1.1.1
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
- Using SQLFire with Hibernate
- 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 run
- 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, Statistics, and User 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 9
Designing vFabric SQLFire Databases
Unlike in traditional database design, SQLFire requires the designer to analyze the common access patterns and choose
a partitioning strategy that results in queries that are pruned to a single partition. In addition, fact tables may need to
be replicated in order to make data available for join operations against partitioned data. This chapter describes the
basic table design principles that you can use to achieve linear scaling with SQLFire.
Design Principles of Scalable, Partition-Aware Databases
A key design principle for linear scaling is a partitioning strategy that allows most data access (queries) to be
pruned to a single partition, thus avoiding expensive locking or latching across multiple partitions during query
execution.
In a highly concurrent system having thousands of connections, multiple queries are uniformly spread across
the entire data set (and therefore across all partitions), and increasing the number of data stores enables linear
scalability. Given sufficient network performance, more connections can be supported without degrading the
response time.
Note: SQLFire supports distributed queries by parallelizing the query execution across data stores.
However, each query instance on a partition can only join rows that are collocated with the partitioned
data. This means that queries can join rows between a partitioned table and any number of replicated
tables hosted on the data store with no restrictions. But queries that join multiple, partitioned tables have
to be filtered based on the partitioning key. Query examples are provided in this section and in Query
Capabilities and Limitations on page 710.
Identify Entity Groups and Partitioning Keys
In relational database terms, an entity group corresponds to rows that are related to one another through foreign
key relationships. Members of an entity group are typically related by parent-child relationships and can be
managed in a single partition. To design a SQLFire database for data partitioning, begin by identifying "entity
groups" and their associated partitioning keys.
For example:
• In a customer order management system, most transactions operate on data related to a single customer at a
time. Queries frequently join a customer's billing information with their orders and shipping information. For
this type of application, you partition related tables using the customer identity. Any customer row along with
their "order" and "shipping" rows forms a single entity group having the customer ID as the entity group identity
(partitioning key). Partitioning related tables using the customer identity enables you to scale the system linearly
as you add more members to support additional customers.
• In a system that manages a comprehensive product catalog (product categories, product specifications, customer
reviews, rebates, related products, and so forth) most data access focuses on a single product at a time. In such
a system, you would partition your data on the product key.
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