Relations Relations and Oracle CEP Tuple Kind Indicator
1.1.2 Relation-to-Relation Operators
The relation-to-relation operators in Oracle CQL are derived from traditional relational queries expressed in SQL. Anywhere a traditional relation is referenced in a SQL query, a relation can be referenced in Oracle CQL. Consider the following examples for a stream CarSegStr with schema: car_id integer, speed integer, exp_way integer, lane integer, dir integer, and seg integer. In Example 1–7 , at any time instant, the output relation of this query contains the set of vehicles having transmitted a position-speed measurement within the last 30 seconds. Example 1–7 Relation-to-Relation Operation processor namecqlProcessorname rules view id=CurCarSeg schema=car_id exp_way lane dir seg[CDATA[ select distinct car_id, exp_way, lane, dir, seg from CarSegStr [range 30 seconds] ]]query rules processor The distinct operator is the relation-to-relation operator. Using distinct, Oracle CEP returns only one copy of each set of duplicate tuples selected. Duplicate tuples are those with matching values for each expression in the select list. You can use distinct in a select_clause and with aggregate functions. For more information on distinct, see: ■ Chapter 9, Built-In Aggregate Functions ■ select_clause::= on page 20-31.1.3 Stream-to-Relation Operators Windows
Oracle CQL supports stream-to-relation operations based on a sliding window. In general, S[W] is a relation. At time T the relation contains all tuples in window W applied to stream S up to T. Introduction to Oracle CQL 1-9 window_type::= Oracle CQL supports the following built-in window types: ■ Range: time-based S[Range T], or, optionally, S[Range T1 Slide T2] ■ Range: time-based unbounded S[Range Unbounded] ■ Range: time-based now S[Now] ■ Range: constant value S[Range C on ID] ■ Tuple-based: S[Rows N], or, optionally, S[Rows N1 Slide N2] ■ Partitioned: S[Partition By A1 ... Ak Rows N] or, optionally, S[Partition By A1 ... Ak Rows N Range T], or S[Partition By A1 ... Ak Rows N Range T1 Slide T2] This section describes the following stream-to-relation operator properties: ■ Section 1.1.3.1, Range, Rows, and Slide ■ Section 1.1.3.2, Partition ■ Section 1.1.3.3, Default Stream-to-Relation Operator For more information, see: ■ Range-Based Stream-to-Relation Window Operators on page 4-6 ■ Tuple-Based Stream-to-Relation Window Operators on page 4-13 ■ Partitioned Stream-to-Relation Window Operators on page 4-181.1.3.1 Range, Rows, and Slide
The keywords Range and Rows specify how much data you want to query:Parts
» Oracle Fusion Middleware Online Documentation Library
» Streams and Channels Oracle CEP represents a stream as a channel as
» Channel Schema The event source you connect to a stream determines the
» Querying a Channel Once the event source, channel, and processor are
» Controlling Which Queries Output to a Downstream Channel If you specify more
» Relations Relations and Oracle CEP Tuple Kind Indicator
» Range, Rows, and Slide at Query Start-Up and for Empty Relations The descriptions
» Partition Stream-to-Relation Operators Windows
» Default Stream-to-Relation Operator Stream-to-Relation Operators Windows
» Relation-to-Relation Operators Stream-to-Stream Operators
» Event Sources Event Sources and Event Sinks
» Relational Database Table Event Sources
» Function Table Event Sources
» Pattern Recognition Cache Event Sources Functions
» Data Cartridges Fundamentals of Oracle CQL
» Lexical Conventions Oracle CQL Statements
» Oracle CQL and SQL Standards
» Oracle CEP Visualizer Oracle CEP Tools
» Oracle CQL Built-in Datatypes
» Numeric Values Datatype Comparison Rules
» Date Values Datatype Comparison Rules
» Implicit Datatype Conversion Datatype Conversion
» Explicit Datatype Conversion Datatype Conversion
» SQL Datatype Conversion Datatype Conversion
» Oracle Data Cartridge Datatype Conversion
» User-Defined Function Datatype Conversion
» Integer Literals Numeric Literals
» Floating-Point Literals Numeric Literals
» Text Literals Datetime Literals
» Number Format Models Format Models
» Aliases in the relation_variable Clause
» How to Define a Data Type Alias Using the Aliases Element
» Schema Object Naming Guidelines Schema Object Naming Examples
» ELEMENT_TIME for a System-Timestamped Stream
» Using ELEMENT_TIME With SELECT
» Using ELEMENT_TIME With GROUP BY
» Using ELEMENT_TIME With PATTERN
» What You May Need to Know About Unary and Binary Operators
» What You May Need to Know About Operator Precedence
» Comparison Conditions Oracle Fusion Middleware Online Documentation Library
» Logical Conditions Oracle Fusion Middleware Online Documentation Library
» Range Conditions Oracle Fusion Middleware Online Documentation Library
» Null Conditions Compound Conditions
» Using IN and NOT IN as a Set Operation Using IN and NOT IN as a Membership Condition
» Introduction to Common Oracle CQL DDL Clauses
» Introduction to Oracle CQL Built-In Single-Row Functions
» Built-In Aggregate Functions and the Where, Group By, and Having Clauses
» Introduction to Oracle CQLBuilt-In Single-Row Colt Functions
» double c Oracle Fusion Middleware Online Documentation Library
» Introduction to Oracle CQL Built-In java.lang.Math Functions
» User-Defined Single-Row Functions Types of User-Defined Functions
» How to Implement a User-Defined Single-Row Function
» How to Implement a User-Defined Aggregate Function
» Data Cartridge Name Data Cartridge Application Context
» Oracle CQL Data Cartridge Types
» Application Class Space Policy
» No Automatic Import Class Space Policy Server Class Space Policy
» Class Loading Example Class Loading
» Data Cartridge Name Method Resolution
» How to Query Using the Java API How to Query Using Exported Java Classes
» Data Cartridge Name Understanding Oracle Spatial
» Element Info Array Ordinates and Coordinate Systems and the SDO_SRID
» Geometric Relation Operators Scope
» com.oracle.cep.cartridge.spatial.Geometry Methods
» oracle.spatial.geometry.JGeometry Methods The following JGeometry public
» Datatype Mapping Oracle Spatial Application Context
» How to Access the Geometry Types That the Oracle Spatial Java API Supports
» How to Create a Geometry How to Access Geometry Type Public Methods and Fields
» Data Cartridge Name Understanding the Oracle CEP JDBC Data Cartridge
» Scope Understanding the Oracle CEP JDBC Data Cartridge
» Datatype Mapping Understanding the Oracle CEP JDBC Data Cartridge
» function Element Attributes Defining SQL Statements: function Element
» Multiple Parameter JDBC Cartridge Context Functions Using the Oracle CEP
» Overloading JDBC Cartridge Context Functions Using the Oracle CEP JDBC data
» Using SELECT List Aliases Using the TABLE Clause
» Using a Native CQL Type as a return-component-type
» How to Create an Oracle CQL Query
» Where Clause Query Building Blocks
» MATCH_RECOGNIZE Query Queries
» Relational Database Table Query XMLTable Query
» Function TABLE Query Queries
» Sorting Query Results Queries
» Detecting Differences in Query Results
» Parameterized Queries in Oracle CQL Statements
» The bindings Element Parameterized Queries
» Run-Time Query Naming Lexical Conventions for Parameter Values
» Views and Joins Views and Schemas
» Cache Key First and Simple Equality No Arithmetic Operations on Cache Keys
» Oracle CQL Queries and Oracle Data Cartridges
» MATCH_RECOGNIZE and the WHERE Clause Referencing Singleton and Group Matches
» Running Aggregates and Final Aggregates
» Operating on the Same Correlation Variable Referencing Variables That Have not Been Matched Yet
» Using prev Understanding Pattern Recognition With MATCH_RECOGNIZE
» Functions Over Correlation Variables in the MEASURES Clause
» Pattern Quantifiers and Regular Expressions
» Referencing One Correlation Variable From Another in the DEFINE Clause
» PARTITION BY Clause Oracle Fusion Middleware Online Documentation Library
» ORDER BY Clause ALL MATCHES Clause
» WITHIN Clause Oracle Fusion Middleware Online Documentation Library
» Fixed Duration Non-Event Detection
» Recurring Non-Event Detection DURATION Clause
» INCLUDE TIMER EVENTS Clause SUBSET Clause
» Pattern Detection MATCH_RECOGNIZE Examples
» Pattern Detection With PARTITION BY
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