diff --git a/README.md b/README.md index 4725eda90b..e15b6b2a3e 100644 --- a/README.md +++ b/README.md @@ -140,7 +140,7 @@ Install 5.0.0. +Latest API Docs is 5.0.1. ## Contact us * Post your questions with the "Siddhi" tag in Stackoverflow. diff --git a/docs/api/5.0.1.md b/docs/api/5.0.1.md new file mode 100644 index 0000000000..071a3a3bda --- /dev/null +++ b/docs/api/5.0.1.md @@ -0,0 +1,2371 @@ +# API Docs - v5.0.1 + +## Core + +### and *(Aggregate Function)* + +

Returns the results of AND operation for all the events.

+Syntax +``` + and( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe value that needs to be AND operation.BOOLNoYes
+ +Examples +EXAMPLE 1 +``` +from cscStream#window.lengthBatch(10) +select and(isFraud) as isFraudTransaction +insert into alertStream; +``` +

This will returns the result for AND operation of isFraud values as a boolean value for event chunk expiry by window length batch.

+ +### avg *(Aggregate Function)* + +

Calculates the average for all the events.

+Syntax +``` + avg( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe value that need to be averaged.INT
LONG
DOUBLE
FLOAT		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream#window.timeBatch + select avg(temp) as avgTemp + insert into barStream; +``` +

avg(temp) returns the average temp value for all the events based on their arrival and expiry.

+ +### count *(Aggregate Function)* + +

Returns the count of all the events.

+Syntax +``` + count() + count( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThis function accepts one parameter. It can belong to any one of the available types.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		YesYes
+ +Examples +EXAMPLE 1 +``` +from fooStream#window.timeBatch(10 sec) +select count() as count +insert into barStream; +``` +

This will return the count of all the events for time batch in 10 seconds.

+ +### distinctCount *(Aggregate Function)* + +

This returns the count of distinct occurrences for a given arg.

+Syntax +``` + distinctCount( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe object for which the number of distinct occurences needs to be counted.INT
LONG
DOUBLE
FLOAT
STRING		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select distinctcount(pageID) as count +insert into barStream; +``` +

distinctcount(pageID) for the following output returns '3' when the available values are as follows.
 "WEB_PAGE_1"
 "WEB_PAGE_1"
 "WEB_PAGE_2"
 "WEB_PAGE_3"
 "WEB_PAGE_1"
 "WEB_PAGE_2"
 The three distinct occurences identified are 'WEB_PAGE_1', 'WEB_PAGE_2', and 'WEB_PAGE_3'.

+ +### max *(Aggregate Function)* + +

Returns the maximum value for all the events.

+Syntax +``` + max( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe value that needs to be compared to find the maximum value.INT
LONG
DOUBLE
FLOAT		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream#window.timeBatch(10 sec) +select max(temp) as maxTemp +insert into barStream; +``` +

max(temp) returns the maximum temp value recorded for all the events based on their arrival and expiry.

+ +### maxForever *(Aggregate Function)* + +

This is the attribute aggregator to store the maximum value for a given attribute throughout the lifetime of the query regardless of any windows in-front.

+Syntax +``` + maxForever( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe value that needs to be compared to find the maximum value.INT
LONG
DOUBLE
FLOAT		NoYes
+ +Examples +EXAMPLE 1 +``` +from inputStream +select maxForever(temp) as max +insert into outputStream; +``` +

maxForever(temp) returns the maximum temp value recorded for all the events throughout the lifetime of the query.

+ +### min *(Aggregate Function)* + +

Returns the minimum value for all the events.

+Syntax +``` + min( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe value that needs to be compared to find the minimum value.INT
LONG
DOUBLE
FLOAT		NoYes
+ +Examples +EXAMPLE 1 +``` +from inputStream +select min(temp) as minTemp +insert into outputStream; +``` +

min(temp) returns the minimum temp value recorded for all the events based on their arrival and expiry.

+ +### minForever *(Aggregate Function)* + +

This is the attribute aggregator to store the minimum value for a given attribute throughout the lifetime of the query regardless of any windows in-front.

+Syntax +``` + minForever( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe value that needs to be compared to find the minimum value.INT
LONG
DOUBLE
FLOAT		NoYes
+ +Examples +EXAMPLE 1 +``` +from inputStream +select minForever(temp) as max +insert into outputStream; +``` +

minForever(temp) returns the minimum temp value recorded for all the events throughoutthe lifetime of the query.

+ +### or *(Aggregate Function)* + +

Returns the results of OR operation for all the events.

+Syntax +``` + or( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe value that needs to be OR operation.BOOLNoYes
+ +Examples +EXAMPLE 1 +``` +from cscStream#window.lengthBatch(10) +select or(isFraud) as isFraudTransaction +insert into alertStream; +``` +

This will returns the result for OR operation of isFraud values as a boolean value for event chunk expiry by window length batch.

+ +### stdDev *(Aggregate Function)* + +

Returns the calculated standard deviation for all the events.

+Syntax +``` + stdDev( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe value that should be used to calculate the standard deviation.INT
LONG
DOUBLE
FLOAT		NoYes
+ +Examples +EXAMPLE 1 +``` +from inputStream +select stddev(temp) as stdTemp +insert into outputStream; +``` +

stddev(temp) returns the calculated standard deviation of temp for all the events based on their arrival and expiry.

+ +### sum *(Aggregate Function)* + +

Returns the sum for all the events.

+Syntax +``` + sum( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe value that needs to be summed.INT
LONG
DOUBLE
FLOAT		NoYes
+ +Examples +EXAMPLE 1 +``` +from inputStream +select sum(volume) as sumOfVolume +insert into outputStream; +``` +

This will returns the sum of volume values as a long value for each event arrival and expiry.

+ +### unionSet *(Aggregate Function)* + +

Union multiple sets.
 This attribute aggregator maintains a union of sets. The given input set is put into the union set and the union set is returned.

+Syntax +``` + unionSet( set) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
setThe java.util.Set object that needs to be added into the union set.OBJECTNoYes
+ +Examples +EXAMPLE 1 +``` +from stockStream +select createSet(symbol) as initialSet +insert into initStream + +from initStream#window.timeBatch(10 sec) +select unionSet(initialSet) as distinctSymbols +insert into distinctStockStream; +``` +

distinctStockStream will return the set object which contains the distinct set of stock symbols received during a sliding window of 10 seconds.

+ +### UUID *(Function)* + +

Generates a UUID (Universally Unique Identifier).

+Syntax +``` + UUID() +``` + +Examples +EXAMPLE 1 +``` +from TempStream +select convert(roomNo, 'string') as roomNo, temp, UUID() as messageID +insert into RoomTempStream; +``` +

This will converts a room number to string, introducing a message ID to each event asUUID() returns a34eec40-32c2-44fe-8075-7f4fde2e2dd8

from TempStream
select convert(roomNo, 'string') as roomNo, temp, UUID() as messageID
insert into RoomTempStream;

+ +### cast *(Function)* + +

Converts the first parameter according to the cast.to parameter. Incompatible arguments cause Class Cast exceptions if further processed. This function is used with map extension that returns attributes of the object type. You can use this function to cast the object to an accurate and concrete type.

+Syntax +``` + cast( to.be.caster, cast.to) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
to.be.casterThis specifies the attribute to be casted.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
cast.toA string constant parameter expressing the cast to type using one of the following strings values: int, long, float, double, string, bool.STRINGNoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select symbol as name, cast(temp, 'double') as temp +insert into barStream; +``` +

This will cast the fooStream temp field value into 'double' format.

+ +### coalesce *(Function)* + +

Returns the value of the first input parameter that is not null, and all input parameters have to be on the same type.

+Syntax +``` + coalesce( arg, ...) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThis function accepts one or more parameters. They can belong to any one of the available types. All the specified parameters should be of the same type.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select coalesce('123', null, '789') as value +insert into barStream; +``` +

This will returns first null value 123.

+ +EXAMPLE 2 +``` +from fooStream +select coalesce(null, 76, 567) as value +insert into barStream; +``` +

This will returns first null value 76.

+ +EXAMPLE 3 +``` +from fooStream +select coalesce(null, null, null) as value +insert into barStream; +``` +

This will returns null as there are no notnull values.

+ +### convert *(Function)* + +

Converts the first input parameter according to the convertedTo parameter.

+Syntax +``` + convert( to.be.converted, converted.to) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
to.be.convertedThis specifies the value to be converted.INT
LONG
DOUBLE
FLOAT
STRING
BOOL		NoYes
converted.toA string constant parameter to which type the attribute need to be converted using one of the following strings values: 'int', 'long', 'float', 'double', 'string', 'bool'.STRINGNoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select convert(temp, 'double') as temp +insert into barStream; +``` +

This will convert fooStream temp value into 'double'.

+ +EXAMPLE 2 +``` +from fooStream +select convert(temp, 'int') as temp +insert into barStream; +``` +

This will convert fooStream temp value into 'int' (value = "convert(45.9, 'int') returns 46").

+ +### createSet *(Function)* + +

Includes the given input parameter in a java.util.HashSet and returns the set.

+Syntax +``` + createSet( input) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
inputThe input that needs to be added into the set.INT
LONG
DOUBLE
FLOAT
STRING
BOOL		NoYes
+ +Examples +EXAMPLE 1 +``` +from stockStream +select createSet(symbol) as initialSet +insert into initStream; +``` +

For every incoming stockStream event, the initStream stream will produce a set object having only one element: the symbol in the incoming stockStream.

+ +### currentTimeMillis *(Function)* + +

Returns the current timestamp of siddhi application in milliseconds.

+Syntax +``` + currentTimeMillis() +``` + +Examples +EXAMPLE 1 +``` +from fooStream +select symbol as name, currentTimeMillis() as eventTimestamp +insert into barStream; +``` +

This will extract current siddhi application timestamp.

+ +### default *(Function)* + +

Checks if the 'attribute' parameter is null and if so returns the value of the 'default' parameter

+Syntax +``` + default( attribute, default) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
attributeThe attribute that could be null.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
defaultThe default value that will be used when 'attribute' parameter is nullINT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
+ +Examples +EXAMPLE 1 +``` +from TempStream +select default(temp, 0.0) as temp, roomNum +insert into StandardTempStream; +``` +

This will replace TempStream's temp attribute with default value if the temp is null.

+ +### eventTimestamp *(Function)* + +

Returns the timestamp of the processed event.

+Syntax +``` + eventTimestamp() +``` + +Examples +EXAMPLE 1 +``` +from fooStream +select symbol as name, eventTimestamp() as eventTimestamp +insert into barStream; +``` +

This will extract current events timestamp.

+ +### ifThenElse *(Function)* + +

Evaluates the 'condition' parameter and returns value of the 'if.expression' parameter if the condition is true, or returns value of the 'else.expression' parameter if the condition is false. Here both 'if.expression' and 'else.expression' should be of the same type.

+Syntax +``` + ifThenElse( condition, if.expression, else.expression) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
conditionThis specifies the if then else condition value.BOOLNoYes
if.expressionThis specifies the value to be returned if the value of the condition parameter is true.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
else.expressionThis specifies the value to be returned if the value of the condition parameter is false.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
+ +Examples +EXAMPLE 1 +``` +@info(name = 'query1') +from sensorEventStream +select sensorValue, ifThenElse(sensorValue>35,'High','Low') as status +insert into outputStream; +``` +

This will returns High if sensorValue = 50.

+ +EXAMPLE 2 +``` +@info(name = 'query1') +from sensorEventStream +select sensorValue, ifThenElse(voltage < 5, 0, 1) as status +insert into outputStream; +``` +

This will returns 1 if voltage= 12.

+ +EXAMPLE 3 +``` +@info(name = 'query1') +from userEventStream +select userName, ifThenElse(password == 'admin', true, false) as passwordState +insert into outputStream; +``` +

This will returns passwordState as true if password = admin.

+ +### instanceOfBoolean *(Function)* + +

Checks whether the parameter is an instance of Boolean or not.

+Syntax +``` + instanceOfBoolean( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe parameter to be checked.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select instanceOfBoolean(switchState) as state +insert into barStream; +``` +

This will return true if the value of switchState is true.

+ +EXAMPLE 2 +``` +from fooStream +select instanceOfBoolean(value) as state +insert into barStream; +``` +

if the value = 32 then this will returns false as the value is not an instance of the boolean.

+ +### instanceOfDouble *(Function)* + +

Checks whether the parameter is an instance of Double or not.

+Syntax +``` + instanceOfDouble( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe parameter to be checked.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select instanceOfDouble(value) as state +insert into barStream; +``` +

This will return true if the value field format is double ex : 56.45.

+ +EXAMPLE 2 +``` +from fooStream +select instanceOfDouble(switchState) as state +insert into barStream; +``` +

if the switchState = true then this will returns false as the value is not an instance of the double.

+ +### instanceOfFloat *(Function)* + +

Checks whether the parameter is an instance of Float or not.

+Syntax +``` + instanceOfFloat( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe parameter to be checked.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select instanceOfFloat(value) as state +insert into barStream; +``` +

This will return true if the value field format is float ex : 56.45f.

+ +EXAMPLE 2 +``` +from fooStream +select instanceOfFloat(switchState) as state +insert into barStream; +``` +

if the switchState = true then this will returns false as the value is an instance of the boolean not a float.

+ +### instanceOfInteger *(Function)* + +

Checks whether the parameter is an instance of Integer or not.

+Syntax +``` + instanceOfInteger( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe parameter to be checked.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select instanceOfInteger(value) as state +insert into barStream; +``` +

This will return true if the value field format is integer.

+ +EXAMPLE 2 +``` +from fooStream +select instanceOfInteger(switchState) as state +insert into barStream; +``` +

if the switchState = true then this will returns false as the value is an instance of the boolean not a long.

+ +### instanceOfLong *(Function)* + +

Checks whether the parameter is an instance of Long or not.

+Syntax +``` + instanceOfLong( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe parameter to be checked.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select instanceOfLong(value) as state +insert into barStream; +``` +

This will return true if the value field format is long ex : 56456l.

+ +EXAMPLE 2 +``` +from fooStream +select instanceOfLong(switchState) as state +insert into barStream; +``` +

if the switchState = true then this will returns false as the value is an instance of the boolean not a long.

+ +### instanceOfString *(Function)* + +

Checks whether the parameter is an instance of String or not.

+Syntax +``` + instanceOfString( arg) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThe parameter to be checked.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		NoYes
+ +Examples +EXAMPLE 1 +``` +from fooStream +select instanceOfString(value) as state +insert into barStream; +``` +

This will return true if the value field format is string ex : 'test'.

+ +EXAMPLE 2 +``` +from fooStream +select instanceOfString(switchState) as state +insert into barStream; +``` +

if the switchState = true then this will returns false as the value is an instance of the boolean not a string.

+ +### maximum *(Function)* + +

Returns the maximum value of the input parameters.

+Syntax +``` + maximum( arg, ...) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThis function accepts one or more parameters. They can belong to any one of the available types. All the specified parameters should be of the same type.INT
LONG
DOUBLE
FLOAT		NoYes
+ +Examples +EXAMPLE 1 +``` +@info(name = 'query1') from inputStream +select maximum(price1, price2, price3) as max +insert into outputStream; +``` +

This will returns the maximum value of the input parameters price1, price2, price3.

+ +### minimum *(Function)* + +

Returns the minimum value of the input parameters.

+Syntax +``` + minimum( arg, ...) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThis function accepts one or more parameters. They can belong to any one of the available types. All the specified parameters should be of the same type.INT
LONG
DOUBLE
FLOAT		NoYes
+ +Examples +EXAMPLE 1 +``` +@info(name = 'query1') from inputStream +select maximum(price1, price2, price3) as max +insert into outputStream; +``` +

This will returns the minimum value of the input parameters price1, price2, price3.

+ +### sizeOfSet *(Function)* + +

Returns the size of an object of type java.util.Set.

+Syntax +``` + sizeOfSet( set) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
setThe set object. This parameter should be of type java.util.Set. A set object may be created by the 'set' attribute aggregator in Siddhi. OBJECTNoYes
+ +Examples +EXAMPLE 1 +``` +from stockStream +select initSet(symbol) as initialSet +insert into initStream; + +;from initStream#window.timeBatch(10 sec) +select union(initialSet) as distinctSymbols +insert into distinctStockStream; + +from distinctStockStream +select sizeOfSet(distinctSymbols) sizeOfSymbolSet +insert into sizeStream; +``` +

The sizeStream stream will output the number of distinct stock symbols received during a sliding window of 10 seconds.

+ +### pol2Cart *(Stream Function)* + +

The pol2Cart function calculating the cartesian coordinates x & y for the given theta, rho coordinates and adding them as new attributes to the existing events.

+Syntax +``` +pol2Cart() +pol2Cart( theta, rho) +pol2Cart( theta, rho, z) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
thetaThe theta value of the coordinates.DOUBLENoYes
rhoThe rho value of the coordinates.DOUBLENoYes
zz value of the cartesian coordinates.If z value is not given, drop the third parameter of the output.DOUBLEYesYes
+ +Examples +EXAMPLE 1 +``` +from PolarStream#pol2Cart(theta, rho) +select x, y +insert into outputStream ; +``` +

This will return cartesian coordinates (4.99953024681082, 0.06853693328228748) for theta: 0.7854 and rho: 5.

+ +EXAMPLE 2 +``` +from PolarStream#pol2Cart(theta, rho, 3.4) +select x, y, z +insert into outputStream ; +``` +

This will return cartesian coordinates (4.99953024681082, 0.06853693328228748, 3.4)for theta: 0.7854 and rho: 5 and z: 3.4.

+ +### log *(Stream Processor)* + +

The logger logs the message on the given priority with or without processed event.

+Syntax +``` +log() +log( log.message) +log( is.event.logged) +log( log.message, is.event.logged) +log( priority, log.message) +log( priority, log.message, is.event.logged) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
priorityThe priority/type of this log message (INFO, DEBUG, WARN, FATAL, ERROR, OFF, TRACE).INFOSTRINGYesNo
log.messageThis message will be logged. :STRINGYesYes
is.event.loggedTo log the processed event.trueBOOLYesNo
+ +Examples +EXAMPLE 1 +``` +from fooStream#log("INFO", "Sample Event :", true) +select * +insert into barStream; +``` +

This will log as INFO with the message "Sample Event :" + fooStream:events.

+ +EXAMPLE 2 +``` +from fooStream#log("Sample Event :", true) +select * +insert into barStream; +``` +

This will logs with default log level as INFO.

+ +EXAMPLE 3 +``` +from fooStream#log("Sample Event :", fasle) +select * +insert into barStream; +``` +

This will only log message.

+ +EXAMPLE 4 +``` +from fooStream#log(true) +select * +insert into barStream; +``` +

This will only log fooStream:events.

+ +EXAMPLE 5 +``` +from fooStream#log() +select * +insert into barStream; +``` +

This will only log fooStream:events.

+ +EXAMPLE 6 +``` +from fooStream#log("Sample Event :") +select * +insert into barStream; +``` +

This will log message and fooStream:events.

+ +### batch *(Window)* + +

A window that holds an incoming events batch. When a new set of events arrives, the previously arrived old events will be expired. Batch window can be used to aggregate events that comes in batches. If it has the parameter length specified, then batch window process the batch as several chunks.

+Syntax +``` +batch() +batch( window.length) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
window.lengthThe length of a chunkIf length value was not given it assign 0 as length and process the whole batch as onceINTYesNo
+ +Examples +EXAMPLE 1 +``` +define stream consumerItemStream (itemId string, price float) + +from consumerItemStream#window.batch() +select price, str:groupConcat(itemId) as itemIds +group by price +insert into outputStream; +``` +

This will output comma separated items IDs that have the same price for each incoming batch of events.

+ +### cron *(Window)* + +

This window outputs the arriving events as and when they arrive, and resets (expires) the window periodically based on the given cron expression.

+Syntax +``` +cron( cron.expression) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
cron.expressionThe cron expression that resets the window.STRINGNoNo
+ +Examples +EXAMPLE 1 +``` +define stream InputEventStream (symbol string, price float, volume int); + +@info(name = 'query1') +from InputEventStream#cron('*/5 * * * * ?') +select symbol, sum(price) as totalPrice +insert into OutputStream; +``` +

This let the totalPrice to gradually increase and resets to zero as a batch every 5 seconds.

+ +EXAMPLE 2 +``` +define stream StockEventStream (symbol string, price float, volume int) +define window StockEventWindow (symbol string, price float, volume int) cron('*/5 * * * * ?'); + +@info(name = 'query0') +from StockEventStream +insert into StockEventWindow; + +@info(name = 'query1') +from StockEventWindow +select symbol, sum(price) as totalPrice +insert into OutputStream ; +``` +

The defined window will let the totalPrice to gradually increase and resets to zero as a batch every 5 seconds.

+ +### delay *(Window)* + +

A delay window holds events for a specific time period that is regarded as a delay period before processing them.

+Syntax +``` +delay( window.delay) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
window.delayThe time period (specified in sec, min, ms) for which the window should delay the events.INT
LONG
TIME		NoNo
+ +Examples +EXAMPLE 1 +``` +define window delayWindow(symbol string, volume int) delay(1 hour); +define stream PurchaseStream(symbol string, volume int); +define stream DeliveryStream(symbol string); +define stream OutputStream(symbol string); + +@info(name='query1') +from PurchaseStream +select symbol, volume +insert into delayWindow; + +@info(name='query2') +from delayWindow join DeliveryStream +on delayWindow.symbol == DeliveryStream.symbol +select delayWindow.symbol +insert into OutputStream; +``` +

In this example, purchase events that arrive in the 'PurchaseStream' stream are directed to a delay window. At any given time, this delay window holds purchase events that have arrived within the last hour. These purchase events in the window are matched by the 'symbol' attribute, with delivery events that arrive in the 'DeliveryStream' stream. This monitors whether the delivery of products is done with a minimum delay of one hour after the purchase.

+ +### externalTime *(Window)* + +

A sliding time window based on external time. It holds events that arrived during the last windowTime period from the external timestamp, and gets updated on every monotonically increasing timestamp.

+Syntax +``` +externalTime( timestamp, window.time) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
timestampThe time which the window determines as current time and will act upon. The value of this parameter should be monotonically increasing.LONGNoYes
window.timeThe sliding time period for which the window should hold events.INT
LONG
TIME		NoNo
+ +Examples +EXAMPLE 1 +``` +define window cseEventWindow (symbol string, price float, volume int) externalTime(eventTime, 20 sec) output expired events; + +@info(name = 'query0') +from cseEventStream +insert into cseEventWindow; + +@info(name = 'query1') +from cseEventWindow +select symbol, sum(price) as price +insert expired events into outputStream ; +``` +

processing events arrived within the last 20 seconds from the eventTime and output expired events.

+ +### externalTimeBatch *(Window)* + +

A batch (tumbling) time window based on external time, that holds events arrived during windowTime periods, and gets updated for every windowTime.

+Syntax +``` +externalTimeBatch( timestamp, window.time) +externalTimeBatch( timestamp, window.time, start.time) +externalTimeBatch( timestamp, window.time, start.time, timeout) +externalTimeBatch( timestamp, window.time, start.time, timeout, replace.with.batchtime) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
timestampThe time which the window determines as current time and will act upon. The value of this parameter should be monotonically increasing.LONGNoYes
window.timeThe batch time period for which the window should hold events.INT
LONG
TIME		NoNo
start.timeUser defined start time. This could either be a constant (of type int, long or time) or an attribute of the corresponding stream (of type long). If an attribute is provided, initial value of attribute would be considered as startTime.Timestamp of first eventINT
LONG
TIME		YesYes
timeoutTime to wait for arrival of new event, before flushing and giving output for events belonging to a specific batch.System waits till an event from next batch arrives to flush current batchINT
LONG
TIME		YesNo
replace.with.batchtimeThis indicates to replace the expired event timeStamp as the batch end timeStampSystem waits till an event from next batch arrives to flush current batchBOOLYesNo
+ +Examples +EXAMPLE 1 +``` +define window cseEventWindow (symbol string, price float, volume int) externalTimeBatch(eventTime, 1 sec) output expired events; +@info(name = 'query0') +from cseEventStream +insert into cseEventWindow; +@info(name = 'query1') +from cseEventWindow +select symbol, sum(price) as price +insert expired events into outputStream ; +``` +

This will processing events that arrive every 1 seconds from the eventTime.

+ +EXAMPLE 2 +``` +define window cseEventWindow (symbol string, price float, volume int) externalTimeBatch(eventTime, 20 sec, 0) output expired events; +``` +

This will processing events that arrive every 1 seconds from the eventTime. Starts on 0th millisecond of an hour.

+ +EXAMPLE 3 +``` +define window cseEventWindow (symbol string, price float, volume int) externalTimeBatch(eventTime, 2 sec, eventTimestamp, 100) output expired events; +``` +

This will processing events that arrive every 2 seconds from the eventTim. Considers the first event's eventTimestamp value as startTime. Waits 100 milliseconds for the arrival of a new event before flushing current batch.

+ +### frequent *(Window)* + +

This window returns the latest events with the most frequently occurred value for a given attribute(s). Frequency calculation for this window processor is based on Misra-Gries counting algorithm.

+Syntax +``` +frequent( event.count) +frequent( event.count, attribute) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
event.countThe number of most frequent events to be emitted to the stream.INTNoNo
attributeThe attributes to group the events. If no attributes are given, the concatenation of all the attributes of the event is considered.The concatenation of all the attributes of the event is considered.STRINGYesYes
+ +Examples +EXAMPLE 1 +``` +@info(name = 'query1') +from purchase[price >= 30]#window.frequent(2) +select cardNo, price +insert all events into PotentialFraud; +``` +

This will returns the 2 most frequent events.

+ +EXAMPLE 2 +``` +@info(name = 'query1') +from purchase[price >= 30]#window.frequent(2, cardNo) +select cardNo, price +insert all events into PotentialFraud; +``` +

This will returns the 2 latest events with the most frequently appeared card numbers.

+ +### length *(Window)* + +

A sliding length window that holds the last 'window.length' events at a given time, and gets updated for each arrival and expiry.

+Syntax +``` +length( window.length) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
window.lengthThe number of events that should be included in a sliding length window.INTNoNo
+ +Examples +EXAMPLE 1 +``` +define window StockEventWindow (symbol string, price float, volume int) length(10) output all events; + +@info(name = 'query0') +from StockEventStream +insert into StockEventWindow; +@info(name = 'query1') + +from StockEventWindow +select symbol, sum(price) as price +insert all events into outputStream ; +``` +

This will process last 10 events in a sliding manner.

+ +### lengthBatch *(Window)* + +

A batch (tumbling) length window that holds and process a number of events as specified in the window.length.

+Syntax +``` +lengthBatch( window.length) +lengthBatch( window.length, stream.current.event) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
window.lengthThe number of events the window should tumble.INTNoNo
stream.current.eventLet the window stream the current events out as and when they arrive to the window while expiring them in batches.falseBOOLYesNo
+ +Examples +EXAMPLE 1 +``` +define stream InputEventStream (symbol string, price float, volume int); + +@info(name = 'query1') +from InputEventStream#lengthBatch(10) +select symbol, sum(price) as price +insert into OutputStream; +``` +

This collect and process 10 events as a batch and output them.

+ +EXAMPLE 2 +``` +define stream InputEventStream (symbol string, price float, volume int); + +@info(name = 'query1') +from InputEventStream#lengthBatch(10, true) +select symbol, sum(price) as sumPrice +insert into OutputStream; +``` +

This window sends the arriving events directly to the output letting the sumPrice to increase gradually, after every 10 events it clears the window as a batch and resets the sumPrice to zero.

+ +EXAMPLE 3 +``` +define stream InputEventStream (symbol string, price float, volume int); +define window StockEventWindow (symbol string, price float, volume int) lengthBatch(10) output all events; + +@info(name = 'query0') +from InputEventStream +insert into StockEventWindow; + +@info(name = 'query1') +from StockEventWindow +select symbol, sum(price) as price +insert all events into OutputStream ; +``` +

This uses an defined window to process 10 events as a batch and output all events.

+ +### lossyFrequent *(Window)* + +

This window identifies and returns all the events of which the current frequency exceeds the value specified for the supportThreshold parameter.

+Syntax +``` +lossyFrequent( support.threshold) +lossyFrequent( support.threshold, error.bound) +lossyFrequent( support.threshold, error.bound, attribute) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
support.thresholdThe support threshold value.DOUBLENoNo
error.boundThe error bound value.DOUBLENoNo
attributeThe attributes to group the events. If no attributes are given, the concatenation of all the attributes of the event is considered.The concatenation of all the attributes of the event is considered.STRINGYesYes
+ +Examples +EXAMPLE 1 +``` +define stream purchase (cardNo string, price float); +define window purchaseWindow (cardNo string, price float) lossyFrequent(0.1, 0.01); +@info(name = 'query0') +from purchase[price >= 30] +insert into purchaseWindow; +@info(name = 'query1') +from purchaseWindow +select cardNo, price +insert all events into PotentialFraud; +``` +

lossyFrequent(0.1, 0.01) returns all the events of which the current frequency exceeds 0.1, with an error bound of 0.01.

+ +EXAMPLE 2 +``` +define stream purchase (cardNo string, price float); +define window purchaseWindow (cardNo string, price float) lossyFrequent(0.3, 0.05, cardNo); +@info(name = 'query0') +from purchase[price >= 30] +insert into purchaseWindow; +@info(name = 'query1') +from purchaseWindow +select cardNo, price +insert all events into PotentialFraud; +``` +

lossyFrequent(0.3, 0.05, cardNo) returns all the events of which the cardNo attributes frequency exceeds 0.3, with an error bound of 0.05.

+ +### session *(Window)* + +

This is a session window that holds events that belong to a specific session. The events that belong to a specific session are identified by a grouping attribute (i.e., a session key). A session gap period is specified to determine the time period after which the session is considered to be expired. A new event that arrives with a specific value for the session key is matched with the session window with the same session key.
 There can be out of order and late arrival of events, these events can arrive after the session is expired, to include those events to the matching session key specify a latency time period that is less than the session gap period.To have aggregate functions with session windows, the events need to be grouped by the session key via a 'group by' clause.

+Syntax +``` +session( window.session) +session( window.session, window.key) +session( window.session, window.key, window.allowed.latency) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
window.sessionThe time period for which the session considered is valid. This is specified in seconds, minutes, or milliseconds (i.e., 'min', 'sec', or 'ms'.INT
LONG
TIME		NoNo
window.keyThe grouping attribute for events.default-keySTRINGYesYes
window.allowed.latencyThis specifies the time period for which the session window is valid after the expiration of the session. The time period specified here should be less than the session time gap (which is specified via the 'window.session' parameter).0INT
LONG
TIME		YesNo
+ +Examples +EXAMPLE 1 +``` +define stream PurchaseEventStream (user string, item_number int, price float, quantity int); + +@info(name='query0) +from PurchaseEventStream#window.session(5 sec, user, 2 sec) +select * +insert all events into OutputStream; +``` +

This query processes events that arrive at the PurchaseEvent input stream. The 'user' attribute is the session key, and the session gap is 5 seconds. '2 sec' is specified as the allowed latency. Therefore, events with the matching user name that arrive 2 seconds after the expiration of the session are also considered when performing aggregations for the session identified by the given user name.

+ +### sort *(Window)* + +

This window holds a batch of events that equal the number specified as the windowLength and sorts them in the given order.

+Syntax +``` +sort( window.length, attribute) +sort( window.length, attribute, order, ...) +sort( window.length, attribute, order, attribute, ...) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
window.lengthThe size of the window length.INTNoNo
attributeThe attribute that should be checked for the order.The concatenation of all the attributes of the event is considered.STRING
DOUBLE
INT
LONG
FLOAT
LONG		YesYes
orderThe order define as "asc" or "desc".ascSTRINGYesNo
+ +Examples +EXAMPLE 1 +``` +define stream cseEventStream (symbol string, price float, volume long); +define window cseEventWindow (symbol string, price float, volume long) sort(2,volume, 'asc'); +@info(name = 'query0') +from cseEventStream +insert into cseEventWindow; +@info(name = 'query1') +from cseEventWindow +select volume +insert all events into outputStream ; +``` +

sort(5, price, 'asc') keeps the events sorted by price in the ascending order. Therefore, at any given time, the window contains the 5 lowest prices.

+ +### time *(Window)* + +

A sliding time window that holds events that arrived during the last windowTime period at a given time, and gets updated for each event arrival and expiry.

+Syntax +``` +time( window.time) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
window.timeThe sliding time period for which the window should hold events.INT
LONG
TIME		NoNo
+ +Examples +EXAMPLE 1 +``` +define window cseEventWindow (symbol string, price float, volume int) time(20) output all events; +@info(name = 'query0') +from cseEventStream +insert into cseEventWindow; +@info(name = 'query1') +from cseEventWindow +select symbol, sum(price) as price +insert all events into outputStream ; +``` +

This will processing events that arrived within the last 20 milliseconds.

+ +### timeBatch *(Window)* + +

A batch (tumbling) time window that holds and process events that arrive during 'window.time' period as a batch.

+Syntax +``` +timeBatch( window.time) +timeBatch( window.time, start.time) +timeBatch( window.time, stream.current.event) +timeBatch( window.time, start.time, stream.current.event) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
window.timeThe batch time period in which the window process the events.INT
LONG
TIME		NoNo
start.timeThis specifies an offset in milliseconds in order to start the window at a time different to the standard time.Timestamp of first eventINT
LONG		YesNo
stream.current.eventLet the window stream the current events out as and when they arrive to the window while expiring them in batches.falseBOOLYesNo
+ +Examples +EXAMPLE 1 +``` +define stream InputEventStream (symbol string, price float, volume int); + +@info(name = 'query1') +from InputEventStream#timeBatch(20 sec) +select symbol, sum(price) as price +insert into OutputStream; +``` +

This collect and process incoming events as a batch every 20 seconds and output them.

+ +EXAMPLE 2 +``` +define stream InputEventStream (symbol string, price float, volume int); + +@info(name = 'query1') +from InputEventStream#timeBatch(20 sec, true) +select symbol, sum(price) as sumPrice +insert into OutputStream; +``` +

This window sends the arriving events directly to the output letting the sumPrice to increase gradually and on every 20 second interval it clears the window as a batch resetting the sumPrice to zero.

+ +EXAMPLE 3 +``` +define stream InputEventStream (symbol string, price float, volume int); +define window StockEventWindow (symbol string, price float, volume int) timeBatch(20 sec) output all events; + +@info(name = 'query0') +from InputEventStream +insert into StockEventWindow; + +@info(name = 'query1') +from StockEventWindow +select symbol, sum(price) as price +insert all events into OutputStream ; +``` +

This uses an defined window to process events arrived every 20 seconds as a batch and output all events.

+ +### timeLength *(Window)* + +

A sliding time window that, at a given time holds the last window.length events that arrived during last window.time period, and gets updated for every event arrival and expiry.

+Syntax +``` +timeLength( window.time, window.length) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
window.timeThe sliding time period for which the window should hold events.INT
LONG
TIME		NoNo
window.lengthThe number of events that should be be included in a sliding length window..INTNoNo
+ +Examples +EXAMPLE 1 +``` +define stream cseEventStream (symbol string, price float, volume int); +define window cseEventWindow (symbol string, price float, volume int) timeLength(2 sec, 10); +@info(name = 'query0') +from cseEventStream +insert into cseEventWindow; +@info(name = 'query1') +from cseEventWindow select symbol, price, volume +insert all events into outputStream; +``` +

window.timeLength(2 sec, 10) holds the last 10 events that arrived during last 2 seconds and gets updated for every event arrival and expiry.

+ +## Sink + +### inMemory *(Sink)* + +

In-memory transport that can communicate with other in-memory transports within the same JVM, itis assumed that the publisher and subscriber of a topic uses same event schema (stream definition).

+Syntax +``` +@sink(type="inMemory", topic="", @map(...))) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
topicEvent will be delivered to allthe subscribers of the same topicSTRINGNoNo
+ +Examples +EXAMPLE 1 +``` +@sink(type='inMemory', @map(type='passThrough')) +define stream BarStream (symbol string, price float, volume long) +``` +

In this example BarStream uses inMemory transport which emit the Siddhi events internally without using external transport and transformation.

+ +### log *(Sink)* + +

This is a sink that can be used as a logger. This will log the output events in the output stream with user specified priority and a prefix

+Syntax +``` +@sink(type="log", priority="", prefix="", @map(...))) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
priorityThis will set the logger priority i.e log level. Accepted values are INFO, DEBUG, WARN, FATAL, ERROR, OFF, TRACEINFOSTRINGYesNo
prefixThis will be the prefix to the output message. If the output stream has event [2,4] and the prefix is given as "Hello" then the log will show "Hello : [2,4]"default prefix will be : STRINGYesNo
+ +Examples +EXAMPLE 1 +``` +@sink(type='log', prefix='My Log', priority='DEBUG') +define stream BarStream (symbol string, price float, volume long) +``` +

In this example BarStream uses log sink and the prefix is given as My Log. Also the priority is set to DEBUG.

+ +EXAMPLE 2 +``` +@sink(type='log', priority='DEBUG') +define stream BarStream (symbol string, price float, volume long) +``` +

In this example BarStream uses log sink and the priority is set to DEBUG. User has not specified prefix so the default prefix will be in the form <Siddhi App Name> : <Stream Name>

+ +EXAMPLE 3 +``` +@sink(type='log', prefix='My Log') +define stream BarStream (symbol string, price float, volume long) +``` +

In this example BarStream uses log sink and the prefix is given as My Log. User has not given a priority so it will be set to default INFO.

+ +EXAMPLE 4 +``` +@sink(type='log') +define stream BarStream (symbol string, price float, volume long) +``` +

In this example BarStream uses log sink. The user has not given prefix or priority so they will be set to their default values.

+ +## Sinkmapper + +### passThrough *(Sink Mapper)* + +

Pass-through mapper passed events (Event[]) through without any mapping or modifications.

+Syntax +``` +@sink(..., @map(type="passThrough") +``` + +Examples +EXAMPLE 1 +``` +@sink(type='inMemory', @map(type='passThrough')) +define stream BarStream (symbol string, price float, volume long); +``` +

In the following example BarStream uses passThrough outputmapper which emit Siddhi event directly without any transformation into sink.

+ +## Source + +### inMemory *(Source)* + +

In-memory source that can communicate with other in-memory sinks within the same JVM, it is assumed that the publisher and subscriber of a topic uses same event schema (stream definition).

+Syntax +``` +@source(type="inMemory", topic="", @map(...))) +``` + +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
topicSubscribes to sent on the given topic.STRINGNoNo
+ +Examples +EXAMPLE 1 +``` +@source(type='inMemory', @map(type='passThrough')) +define stream BarStream (symbol string, price float, volume long) +``` +

In this example BarStream uses inMemory transport which passes the received event internally without using external transport.

+ +## Sourcemapper + +### passThrough *(Source Mapper)* + +

Pass-through mapper passed events (Event[]) through without any mapping or modifications.

+Syntax +``` +@source(..., @map(type="passThrough") +``` + +Examples +EXAMPLE 1 +``` +@source(type='tcp', @map(type='passThrough')) +define stream BarStream (symbol string, price float, volume long); +``` +

In this example BarStream uses passThrough inputmapper which passes the received Siddhi event directly without any transformation into source.

+ diff --git a/docs/api/latest.md b/docs/api/latest.md index 3135cb5069..071a3a3bda 100644 --- a/docs/api/latest.md +++ b/docs/api/latest.md @@ -1,4 +1,4 @@ -# API Docs - v5.0.1-SNAPSHOT +# API Docs - v5.0.1 ## Core @@ -26,7 +26,7 @@ BOOL No - No + Yes @@ -63,7 +63,7 @@ insert into alertStream; INT
LONG
DOUBLE
FLOAT No - No + Yes @@ -82,8 +82,29 @@ from fooStream#window.timeBatch Syntax ``` count() + count( arg) ``` +QUERY PARAMETERS + + + + + + + + + + + + + + + + + +
NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
argThis function accepts one parameter. It can belong to any one of the available types.INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT		YesYes
+ Examples EXAMPLE 1 ``` @@ -117,7 +138,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING No - No + Yes @@ -154,7 +175,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT No - No + Yes @@ -191,7 +212,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT No - No + Yes @@ -228,7 +249,7 @@ insert into outputStream; INT
LONG
DOUBLE
FLOAT No - No + Yes @@ -265,7 +286,7 @@ insert into outputStream; INT
LONG
DOUBLE
FLOAT No - No + Yes @@ -302,7 +323,7 @@ insert into outputStream; BOOL No - No + Yes @@ -339,7 +360,7 @@ insert into alertStream; INT
LONG
DOUBLE
FLOAT No - No + Yes @@ -376,7 +397,7 @@ insert into outputStream; INT
LONG
DOUBLE
FLOAT No - No + Yes @@ -413,7 +434,7 @@ insert into outputStream; OBJECT No - No + Yes @@ -471,7 +492,7 @@ insert into RoomTempStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes cast.to @@ -479,7 +500,7 @@ insert into RoomTempStream; STRING No - No + Yes @@ -497,7 +518,7 @@ insert into barStream;

Returns the value of the first input parameter that is not null, and all input parameters have to be on the same type.

Syntax ``` - coalesce( args) + coalesce( arg, ...) ``` QUERY PARAMETERS @@ -511,12 +532,12 @@ insert into barStream; Dynamic - args + arg This function accepts one or more parameters. They can belong to any one of the available types. All the specified parameters should be of the same type. INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes @@ -569,7 +590,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL No - No + Yes converted.to @@ -577,7 +598,7 @@ insert into barStream; STRING No - No + Yes @@ -622,7 +643,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL No - No + Yes @@ -676,7 +697,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes default @@ -684,7 +705,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes @@ -738,7 +759,7 @@ insert into barStream; BOOL No - No + Yes if.expression @@ -746,7 +767,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes else.expression @@ -754,7 +775,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes @@ -810,7 +831,7 @@ insert into outputStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes @@ -855,7 +876,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes @@ -900,7 +921,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes @@ -945,7 +966,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes @@ -990,7 +1011,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes @@ -1035,7 +1056,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT
STRING
BOOL
OBJECT No - No + Yes @@ -1061,7 +1082,7 @@ insert into barStream;

Returns the maximum value of the input parameters.

Syntax ``` - maximum( arg) + maximum( arg, ...) ``` QUERY PARAMETERS @@ -1080,7 +1101,7 @@ insert into barStream; INT
LONG
DOUBLE
FLOAT No - No + Yes @@ -1098,7 +1119,7 @@ insert into outputStream;

Returns the minimum value of the input parameters.

Syntax ``` - minimum( arg) + minimum( arg, ...) ``` QUERY PARAMETERS @@ -1117,7 +1138,7 @@ insert into outputStream; INT
LONG
DOUBLE
FLOAT No - No + Yes @@ -1154,7 +1175,7 @@ insert into outputStream; OBJECT No - No + Yes @@ -1201,7 +1222,7 @@ pol2Cart( theta, rho, z) DOUBLE No - No + Yes rho @@ -1209,7 +1230,7 @@ pol2Cart( theta, rho, z) DOUBLE No - No + Yes z @@ -1217,7 +1238,7 @@ pol2Cart( theta, rho, z) If z value is not given, drop the third parameter of the output. DOUBLE Yes - No + Yes @@ -1275,7 +1296,7 @@ log( priority, log.message, is.event.logged) : STRING Yes - No + Yes is.event.logged @@ -1341,6 +1362,7 @@ insert into barStream;

A window that holds an incoming events batch. When a new set of events arrives, the previously arrived old events will be expired. Batch window can be used to aggregate events that comes in batches. If it has the parameter length specified, then batch window process the batch as several chunks.

Syntax ``` +batch() batch( window.length) ``` @@ -1505,7 +1527,7 @@ externalTime( timestamp, window.time) LONG No - No + Yes window.time @@ -1541,6 +1563,7 @@ insert expired events into outputStream ; externalTimeBatch( timestamp, window.time) externalTimeBatch( timestamp, window.time, start.time) externalTimeBatch( timestamp, window.time, start.time, timeout) +externalTimeBatch( timestamp, window.time, start.time, timeout, replace.with.batchtime) ``` QUERY PARAMETERS @@ -1559,7 +1582,7 @@ externalTimeBatch( timestamp, window.time, LONG No - No + Yes window.time @@ -1575,7 +1598,7 @@ externalTimeBatch( timestamp, window.time, Timestamp of first event INT
LONG
TIME Yes - No + Yes timeout @@ -1585,6 +1608,14 @@ externalTimeBatch( timestamp, window.time, Yes No + + replace.with.batchtime + This indicates to replace the expired event timeStamp as the batch end timeStamp + System waits till an event from next batch arrives to flush current batch + BOOL + Yes + No + Examples @@ -1618,6 +1649,7 @@ define window cseEventWindow (symbol string, price float, volume int) externalTi

This window returns the latest events with the most frequently occurred value for a given attribute(s). Frequency calculation for this window processor is based on Misra-Gries counting algorithm.

Syntax ``` +frequent( event.count) frequent( event.count, attribute) ``` @@ -1645,7 +1677,7 @@ frequent( event.count, attribute) The concatenation of all the attributes of the event is considered. STRING Yes - No + Yes @@ -1830,7 +1862,7 @@ lossyFrequent( support.threshold, error.bound, attribu The concatenation of all the attributes of the event is considered. STRING Yes - No + Yes @@ -1897,7 +1929,7 @@ session( window.session, window.key, win default-key STRING Yes - No + Yes window.allowed.latency @@ -1926,8 +1958,9 @@ insert all events into OutputStream;

This window holds a batch of events that equal the number specified as the windowLength and sorts them in the given order.

Syntax ``` -sort( window.length, attribute) -sort( window.length, attribute, order) +sort( window.length, attribute) +sort( window.length, attribute, order, ...) +sort( window.length, attribute, order, attribute, ...) ``` QUERY PARAMETERS @@ -1952,9 +1985,9 @@ sort( window.length, attribute, order) attribute The attribute that should be checked for the order. The concatenation of all the attributes of the event is considered. - STRING + STRING
DOUBLE
INT
LONG
FLOAT
LONG + Yes Yes - No order diff --git a/docs/extensions.md b/docs/extensions.md new file mode 100644 index 0000000000..4a38a3c6c4 --- /dev/null +++ b/docs/extensions.md @@ -0,0 +1,72 @@ +# Siddhi Extensions + +## Available Extensions + +Following are some pre-written extensions that are supported with Siddhi; + +### Extensions released under Apache 2.0 License +Name | Description +:-- | :-- +execution-approximate | The siddhi-execution-approximate is an extension to Siddhi that performs approximate computing on event streams. +execution-env | The siddhi-execution-env extension is an extension to Siddhi that provides the capability to read environment properties inside Siddhi stream definitions and use it inside queries. Functions of the env extension are as follows.. +execution-extrema | The siddhi-execution-extrema extension is an extension to Siddhi that processes event streams based on different arithmetic properties. Different types of processors are available to extract the extremas from the event streams according to the specified attribute in the stream. +execution-geo | The siddhi-execution-geo extension is an extension to Siddhi that provides geo data related functionality such as checking whether a given geo coordinate is within a predefined geo-fence, etc. Following are the functions of the Geo extension. +execution-graph | The siddhi-execution-graph extension is an extension to Siddhi that provides graph related functionality to Siddhi such as getting size of largest connected component of a graph, maximum clique size of a graph, etc. +execution-kalmanfilter | The siddhi-execution-kalman-filter extension is an extension to Siddhi provides that Kalman filtering capabilities to Siddhi. This allows you to detect outliers of input data. +execution-map | The siddhi-execution-map extension is an extension to Siddhi that provides the capability to send a map object inside Siddhi stream definitions and use it inside queries. The following are the functions of the map extension.. +execution-markov | The siddhi-execution-markov extension is an extension to Siddhi that allows abnormal patterns relating to user activity to be detected when carrying out real time analysis. +execution-math | The siddhi-execution-math is an extension to Siddhi, which provides useful mathematical functions that can make your siddhi queries more flexible. +execution-priority | The siddhi-execution-priority extension is an extension to Siddhi that keeps track of the priority of events in a stream. +execution-regex | The siddhi-execution-regex extension is an extension to Siddhi that provides basic RegEx execution capabilities. +execution-reorder | The siddhi-execution-reorder extension is an extension to Siddhi that is used for reordering events from an unordered event stream. Reorder extension is implemented using the K-Slack and alpha K-Stack algorithms. +execution-sentiment | The siddhi-execution-sentiment extension is an extension to Siddhi that performs sentiment analysis using Afinn Wordlist-based approach. +execution-stats | The siddhi-execution-stats extension is an extension to Siddhi that provides statistical functions for aggregated events. Currently this contains median function which calculate the median of aggregated events. Calculation of median is done for each event arrival and expiry, it is not recommended to use this extension for large window sizes. +execution-streamingml | The siddhi-execution-streamingml is an extension to Siddhi that performs streaming machine learning on event streams. +execution-string | The siddhi-execution-string is an extension to Siddhi that provides basic string handling capabilities such as con-cat, length, convert to lowercase, and replace all. +execution-tensorflow | The siddhi-execution-tensorflow is an extension to Siddhi that adds support for inferences from pre-built TensorFlow SavedModels using Siddhi. +execution-time | The siddhi-execution-time extension is an extension to Siddhi that provides time related functionality to Siddhi such as getting current time, current date, manipulating/formatting dates and etc. +execution-timeseries | The siddhi-execution-timeseries extension is an extension to Siddhi which enables users to forecast and detect outliers in time series data, using Linear Regression Models. +execution-unique | The siddhi-execution-unique extension is an extension to Siddhi that processes event streams based on unique events. Different types of unique windows are available to hold unique events based on the given unique key parameter. +execution-unitconversion | The siddhi-execution-unitconversion extension is an extension to Siddhi that enables conversions of length, mass, time and volume units. +io-cdc | The siddhi-io-cdc extension is an extension to Siddhi. It receives change data from MySQL, MS SQL Server, Postgresql, H2 and Oracle in the key-value format. +io-email | The siddhi-io-email extension is an extension to Siddhi that receives and publishes events via email. Using the extension, events can be published through smtp mail server and received through 'pop3' or 'imap' mail serves. +io-file | The siddhi-io-file extension is an extension to Siddhi which is used to receive/publish event data from/to file. It supports both binary and text formats. +io-http | The siddhi-io-http extension is an extension to Siddhi that allows you to receive and publish events via http and https transports and also allow you perform synchronous request and response. This extension works with WSO2 Stream Processor and with standalone Siddhi. +io-jms | The siddhi-io-jms extension is an extension to Siddhi that used to receive and publishe events via JMS Message. This extension allows users to subscribe to a JMS broker and receive/publish JMS messages. +io-kafka | The siddhi-io-kafka extension is an extension to Siddhi. This implements siddhi kafka source and sink that can be used to receive events from a kafka cluster and to publish events to a kafka cluster. +io-mqtt | The siddhi-io-mqtt is an extension to Siddhi mqtt source and sink implementation,that publish and receive events from mqtt broker. +io-prometheus | The siddhi-io-prometheus extension is an extension to Siddhi. The Prometheus-sink publishes Siddhi events as Prometheus metrics and expose them to Prometheus server. The Prometheus-source retrieves Prometheus metrics from an endpoint and send them as Siddhi events. +io-rabbitmq | The siddhi-io-rabbitmq is an extension to Siddhi that publish and receive events from rabbitmq broker. +io-sqs | The siddhi-io-sqs extension is an extension to Siddhi that used to receive and publish events via AWS SQS Service. This extension allows users to subscribe to a SQS queue and receive/publish SQS messages. +io-tcp | The siddhi-io-tcp extension is an extension to Siddhi that allows to receive and publish events through TCP. +io-twitter | The siddhi-io-twitter extension is an extension to Siddhi. It publishes event data from Twitter Applications in the key-value map format. +io-websocket | The siddhi-io-websocket extension is an extension to Siddhi that allows to receive and publish events through WebSocket. +io-wso2event | The siddhi-io-wso2event extension is an extension to Siddhi that receives and publishes events in the WSO2Event format via Thrift or Binary protocols. +map-binary | The siddhi-map-binary extension is an extension to Siddhi that can be used to convert binary events to/from Siddhi events. +map-csv | The siddhi-map-csv extension is an extension to Siddhi that supports mapping incoming events with csv format to a stream at the source, and mapping a stream to csv format events at the sink. +map-json | The siddhi-map-json extension is an extension to Siddhi which is used to convert JSON message to/from Siddhi events. +map-keyvalue | The siddhi-map-keyvalue extension is an extension to Siddhi that supports mapping incoming events with Key-Value map format to a stream at the source, and mapping a stream to Key-Value map events at the sink. +map-text | The siddhi-map-text extension is an extension to Siddhi that supports mapping incoming text messages to a stream at the source, and mapping a stream to text messages at the sink. +map-wso2event | The siddhi-map-wso2event extension is an extension to Siddhi that can be used to convert WSO2 events to/from Siddhi events. +map-xml | The siddhi-map-xml extension is an extension to Siddhi that supports mapping incoming XML events to a stream at the source, and mapping a stream to XML events at the sink. +script-js | The siddhi-script-js is an extension to Siddhi that allows to include JavaScript functions within the Siddhi Query Language. +store-cassandra | The siddhi-store-cassandra extension is an extension to Siddhi that can be used to persist events to a Cassandra instance of the users choice. Find some useful links below: +store-hbase | The siddhi-store-hbase extension is an extension to Siddhi that can be used to persist events to a HBase instance of the users choice. Find some useful links below: +store-mongodb | The siddhi-store-mongodb extension is an extension to Siddhi that can be used to persist events to a MongoDB instance of the users choice. Find some useful links below: +store-rdbms | The siddhi-store-rdbms extension is an extension to Siddhi that can be used to persist events to an RDBMS instance of the user's choice. +store-redis | The siddhi-store-redis extension is an extension for siddhi redis event table implementation. This extension can be used to persist events to a redis cloud instance of version 4.x.x. +store-solr | The siddhi-store-solr extension is an extension for siddhi Solr event table implementation. This extension can be used to persist events to a Solr cloud instance of version 6.x.x. + +### Extensions released under GPL License +Name | Description +:-- | :-- +execution-geo | The siddhi-gpl-execution-geo extension is an extension to Siddhi that provides geo data related functionality such as checking whether a given geo coordinate is within a predefined geo-fence, etc. +execution-nlp | The siddhi-gpl-execution-nlp extension is an extension to Siddhi that can be used to process natural language. +execution-pmml | The siddhi-gpl-execution-pmml extension is an extension to Siddhi that can be used to process texts based on a PMML processing model. +execution-r | The siddhi-gpl-execution-r extension is an extension to Siddhi that can be used to process events with R scripts. +execution-streamingml | The siddhi-execution-streamingml is an extension to Siddhi that performs streaming machine learning on event streams. + + +## Extension Repositories + +All the extension repositories maintained by WSO2 can be found here diff --git a/docs/index.md b/docs/index.md index e67bf5317c..e15b6b2a3e 100755 --- a/docs/index.md +++ b/docs/index.md @@ -1,5 +1,5 @@ -**Siddhi** - Cloud native stream processing engine -=================================================== +**Siddhi** - Cloud Native Stream Processor +=========================================== [![Jenkins Build Status](https://wso2.org/jenkins/view/wso2-dependencies/job/siddhi/job/siddhi/badge/icon)](https://wso2.org/jenkins/view/wso2-dependencies/job/siddhi/job/siddhi) [![GitHub (pre-)release](https://img.shields.io/github/release/siddhi-io/siddhi/all.svg)](https://github.com/siddhi-io/siddhi/releases) @@ -8,15 +8,33 @@ [![codecov](https://codecov.io/gh/siddhi-io/siddhi/branch/master/graph/badge.svg)](https://codecov.io/gh/siddhi-io/siddhi) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) -[Geting Started](documentation/siddhi-5.x/quckstart-5.x/) | [Download](download/) | [User Guide](documentation/siddhi-5.x/user-guide-introduction-5.x/) | [Contribute](contribution/) +[Geting Started](https://siddhi-io.github.io/siddhi/documentation/siddhi-5.x/quckstart-5.x/) | [Download](https://siddhi-io.github.io/siddhi/download/) | [User Guide](https://siddhi-io.github.io/siddhi/documentation/siddhi-5.x/user-guide-5.x/) | [Contribute](https://siddhi-io.github.io/siddhi/contribution/) Siddhi is a cloud native **_Streaming_** and **_Complex Event Processing_** engine that understands **Streaming SQL queries** in order to capture events from diverse data sources, process them, detect complex conditions, and publish output to various endpoints in real time. -Siddhi can run as an embedded [Java library](documentation/siddhi-5.x/siddhi-as-a-java-library-5.x/), and as a microservice on [bare metal, VM](documentation/siddhi-5.x/siddhi-as-a-local-microservice-5.x/), [Docker](documentation/siddhi-5.x/siddhi-as-a-docker-microservice-5.x/) and natively in [Kubernetes](documentation/siddhi-5.x/siddhi-as-a-kubernetes-microservice-5.x/). It also has a [graphical and text editor](#siddhi-development-environment) for building Streaming Data Integration and Streaming Analytics applications. +Siddhi can run as an embedded [Java library](https://siddhi-io.github.io/siddhi/documentation/siddhi-5.x/siddhi-as-a-java-library-5.x/), and as a micro service on [bare metal, VM](https://siddhi-io.github.io/siddhi/documentation/siddhi-5.x/siddhi-as-a-local-microservice-5.x/), [Docker](https://siddhi-io.github.io/siddhi/documentation/siddhi-5.x/siddhi-as-a-docker-microservice-5.x/) and natively in [Kubernetes](https://siddhi-io.github.io/siddhi/documentation/siddhi-5.x/siddhi-as-a-kubernetes-microservice-5.x/). It also has a [graphical and text editor](#siddhi-development-environment) for building Streaming Data Integration and Streaming Analytics applications. -!!! Info "For more details on Siddhi Cloud Native Stream Processor, please refer [this](https://siddhi.io/)" +## Distributions -## Overview + + Kubernetes + + + Docker + + + Binary + + + Java + + + Source + + +And more [installation options](https://siddhi-io.github.io/siddhi/download/) + +## Overview ![](https://raw.githubusercontent.com/siddhi-io/siddhi/master/docs/images/siddhi-overview.png?raw=true "Overview") @@ -72,7 +90,27 @@ If you are a Siddhi user, we would love to hear more on how you use Siddhi? Plea ## Get Started! -Get started with Siddhi in a few minutes by following the Siddhi Quick Start Guide +Get started with Siddhi in a few minutes by following the Siddhi Quick Start Guide + +## Siddhi Development Environment + +**Siddhi Tooling** + +Siddhi provides siddhi-tooling that supports following features to develop and test stream processing applications: + +* **Text Query Editor** with syntax highlighting and advanced auto completion support. +* **Event Simulator and Debugger** to test Siddhi Applications. + ![](https://raw.githubusercontent.com/siddhi-io/siddhi/master/docs/images/editor/source-editor.png "Source Editor") + +* **Graphical Query Editor** with drag and drop query building support. + ![](https://raw.githubusercontent.com/siddhi-io/siddhi/master/docs/images/editor/graphical-editor.png "Graphical Query Editor") + +**IntelliJ IDEA Plugin** + +Install IDEA plugin to get the following features: + +* **Siddhi Query Editor** with syntax highlighting and with basic auto completion +* **Siddhi Runner and Debugger** support to test Siddhi Application ## Siddhi Versions @@ -102,7 +140,7 @@ Get started with Siddhi in a few minutes by following the 5.0.0. +Latest API Docs is 5.0.1. ## Contact us * Post your questions with the "Siddhi" tag in Stackoverflow. @@ -112,7 +150,23 @@ Latest API Docs is extensions. For more details contact via http://wso2.com/support/ diff --git a/mkdocs.yml b/mkdocs.yml index 2f450646bc..d2b9bcb6ef 100755 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -31,11 +31,12 @@ markdown_extensions: guess_lang: false - pymdownx.tasklist: custom_checkbox: true -- markdown.extensions.attr_list: +- markdown.extensions.attr_list: null pages: - Welcome to Siddhi: index.md - API Docs: - latest: api/latest.md + - 5.0.1: api/5.0.1.md - 5.0.0: api/5.0.0.md - 4.5.11: api/4.5.11.md - 4.5.10: api/4.5.10.md