IBM InfoSphere Streams Version 4.1.0

Operators: SPL standard and specialized toolkits

SPL standard and specialized toolkits > Operators

Operators

ARIMA: DEPRECATED: The com.ibm.streams.timeseries.modeling.ARIMA operator is deprecated and is replaced by the com.ibm.streams.timeseries.modeling.ARIMA2 operator. The deprecated operator might be removed in a future release. The ARIMA operator implements the autoregressive integrated moving average (ARIMA) modeling algorithm.
ARIMA2: The ARIMA2 operator implements the autoregressive integrated moving average (ARIMA) modeling algorithm.
ASN1Encode: The ASN1Encode operator creates ASN.1 DER-encoded data from XML documents that fit to the provided ASN.1 specification. This operator requires a structure definition document, the ASN.1 specification, which describes the ASN.1 data structures. The ASN1Encode operator provides following features: Support the ASN.1-encoding for one or more ASN.1 elements (also called protocol data unit, or PDU) Support of the following ASN.1 constructs: Containers CHOICE, SET, and SEQUENCE Primitive types BIT STRING, BMPString, BOOLEAN, ENUMERATED, GeneralizedTime, GeneralString, GraphicString, IA5String, INTEGER, ISO646String, NULL, NumericString, ObjectDescriptor, OBJECT IDENTIFIER, OCTET STRING, PrintableString, REAL, RELATIVE-OID, T61String, TeletexString, UniversalString, UTCTime, UTF8String, VideotexString, and VisibleString Repetition SET OF and SEQUENCE OF Optional OPTIONAL and DEFAULT (limited to the primitive types) Support of basic constraints verification The ability to send invalid XML documents to an error port.
ASN1Parse: The ASN1Parse operator parses a binary data stream that contains ASN.1-encoded data, extracts parts of the data, and sends the data as tuples to downstream operators.
Aggregate: The Aggregate operator is used to compute user-specified aggregations over tuples that are gathered in a window.
AmericanOptionValue: The AmericanOptionValue type-specific operator is for computing the value of "American-style" options.
AnomalyDetector: The AnomalyDetector operator can detect anomalous subsequences in an incoming data stream.
Associations: Association rules are represented as [x] => [y] where [x] is the rule body or antecedent, and [y] is the rule head or consequent.
AutoForecaster: DEPRECATED: The com.ibm.streams.timeseries.modeling.AutoForecaster operator is deprecated and is replaced by the com.ibm.streams.timeseries.modeling.AutoForecaster2 operator. The deprecated operator might be removed in a future release. The AutoForecaster operator is a forecasting operator, which detects the algorithm that best suits the input time series data in real time and forecasts future time series.
AutoForecaster2: The AutoForecaster2 operator is a forecasting operator, which detects the algorithm that best suits the input time series data in real time and forecasts future time series.
BWListTagger: The BWListTagger operator is capable of tagging incoming domain and IP addresses as either appearing in a blacklist or whitelist.
Barrier: The Barrier operator is used to synchronize tuples from two or more streams.
Beacon: The Beacon operator is a utility source that generates tuples on an ad hoc basis.
BloomFilter: The BloomFilter operator detects duplicate tuples in a memory-efficient way.
CSVParse: The CSVParse operator parses an input line of comma-separated values (CSV) that is received in an rstring type input tuple attribute, splits the line into fields (also called items), and assigns the field values to attributes in the output port schema.
CharacterTransform: The CharacterTransform operator is used to convert from one encoding in blob to another encoding in blob.
Classification: The Classification operator calculates the predicted class and the confidence for each tuple in the input stream and automatically assigns those values to output stream attributes.
Clustering: The Clustering operator calculates the cluster index and clustering score for each tuple in the input stream and automatically assigns those values to output stream attributes.
Compress: The Compress operator is used to compress data in a blob and generate blob output.
ControlNotificationSource: The ControlNotificationSource operator provides a connector between control events and data streams by turning control notifications into tuples.
CrossCorrelate: DEPRECATED: The com.ibm.streams.timeseries.analysis.CrossCorrelate operator is deprecated and is replaced by the com.ibm.streams.timeseries.analysis.CrossCorrelate2 operator. The deprecated operator might be removed in a future release. In signal processing, cross-correlation is a measure of similarity of two time series as a function of a time-lag applied to one of them.
CrossCorrelate2: In signal processing, cross-correlation is a measure of similarity of two time series as a function of a time-lag applied to one of them.
CrossCorrelateMulti: In signal processing, cross-correlation is a measure of similarity of two time series as a function of a time-lag applied to one of them.
Custom: The Custom operator is a special logic-related operator that can receive and send any number of streams and does not do anything by itself.
DB2PartitionedAppend: The DB2PartitionedAppend operator writes data to a table in the specified partition of a partitioned DB2® database.
DB2SplitDB: The DB2SplitDB operator determines the partition to use when you are writing input tuples to a partitioned DB2 database.
DSPFilter: DEPRECATED: The com.ibm.streams.timeseries.analysis.DSPFilter operator is deprecated and is replaced by the com.ibm.streams.timeseries.analysis.DSPFilter2 operator. The deprecated operator might be removed in a future release. The Digital Signal Processing (DSP) filter operator performs a digital filtering operation on an input time series.
DSPFilter2: The Digital Signal Processing (DSP) filter operator performs a digital filtering operation on an input time series.
DSPFilterFinite: The Digital Signal Processing (DSP) filter operator performs a digital filtering operation on an input time series.
DWT: DEPRECATED: The com.ibm.streams.timeseries.analysis.DWT operator is deprecated and is replaced by the com.ibm.streams.timeseries.analysis.DWT2 operator. The deprecated operator might be removed in a future release.
DWT2: The DWT2 operator applies a discrete wavelet transform (DWT) on a vector time series.
DataExplorerPush: The DataExplorerPush operator pushes data from InfoSphere® Streams into IBM® InfoSphere Data Explorer.
DeDuplicate: The DeDuplicate operator suppresses duplicate tuples that are seen within a specified time period.
Decompress: The Decompress operator decompresses data in a blob and generate blob output.
Delay: The Delay operator is used to delay a stream by an amount while it keeps the inter-arrival times of tuples and punctuation intact.
DirectoryScan: The DirectoryScan operator watches a directory, and generates file names on the output, one for each file that is found in the directory.
Distribution: The Distribution operator calculates the quartile distribution for an input time series.
DomainProfiling: The DomainProfiling operator analyzes DNS response traffic and reports whether or not the behaviour of the domain is suspicious.
DynamicFilter: The DynamicFilter is a version of the Filter operator that can decide at run time which input tuples are passed through, based on control input it receives.
EuropeanOptionValue: The EuropeanOptionValue type-specific operator is for computing the value of "European-style" options.
ExceptionCatcher: The ExceptionCatcher operator catches exceptions from fused downstream operators and reports these exceptions via tuples that are sent to its optional second output port.
Export: The Export operator sends a stream from the current application, making it available to Import operators of applications that are running in the same streaming middleware instance.
FFT: The FFT operator applies a Fast Fourier transform (FFT) algorithm on a vector time series.
FIXAcceptor: The FixAcceptor operator functions as the Financial Information eXchange (FIX) Acceptor.
FIXInitiator: The FIXInitiator operator functions as the Financial Information Exchange (FIX) Initiator.
FIXMessageToStream: The FIXMessageToStream operator takes a valid Financial Information eXchange (FIX) Message and converts it to a stream for processing.
FMPFilter: The FMPFilter operator is an adaptive faded-memory polynomial filter.
FileSink: The FileSink operator writes tuples to a file.
FileSource: The FileSource operator reads data from a file and produces tuples as a result.
Filter: The Filter operator removes tuples from a stream by passing along only those tuples that satisfy a user-specified condition.
Format: The Format operator is similar to the FileSink, TCPSink, and UDPSink operators, in that it converts SPL tuples into formatted data.
FunctionEvaluator: The FunctionEvaluator operator applies a function to each value in a time series.
Functor: The Functor operator is used to transform input tuples into output ones, and optionally filter them as in a Filter operator.
GAMLearner: The GAMLearner operator applies the generalized additive model (GAM) algorithm to categorical or continuous time series data.
GAMScorer: The GAMScorer operator applies a generalized additive model to score the input time series values.
GMM: The GMM operator uses a Gaussian mixture model to estimate the probability density function (a smoothed histogram) of a time series.
Gate: The Gate operator is used to control the rate at which tuples are passed through.
Generator: The Generator operator generates a sine, triangular, sawtooth, or a pulse train representation of a time series.
Geofence: The Geofence operator is used to manage user-defined geographical regions called geofences and provide information as entities move in and out of of these regions.
HBASEDelete: The HBASEDelete operator deletes an entry, an entire row, a columnFamily in a row, or a columnFamily, columnQualifier pair in a row from HBASE.
HBASEGet: The HBASEGet operator gets tuples from HBASE.
HBASEIncrement: The HBASEIncrement operator increments the specified HBASE entry.
HBASEPut: The HBASEPut operator puts tuples in HBASE.
HBASEScan: The HBASEScan operator scans an HBASE table.
HDFS2DirectoryScan: The HDFS2DirectoryScan operator scans a Hadoop Distributed File System directory for new or modified files.
HDFS2FileSink: The HDFS2FileSink operator writes files to a Hadoop Distributed File System.
HDFS2FileSource: The HDFS2FileSource operator reads files from a Hadoop Distributed File System (HDFS).
HTTPGetStream: Connects to an HTTP endpoint, reads "chunks" of data and sends it to the output port.
HTTPPost: This operator sends incoming tuples to the specified HTTP server as part of a POST request.
Hangout: The Hangout operator is used to detect a basic pattern about a moving entity's location called a hangout.
HoltWinters: DEPRECATED: The com.ibm.streams.timeseries.modeling.HoltWinters operator is deprecated and is replaced by the com.ibm.streams.timeseries.modeling.HoltWinters2 operator. The deprecated operator might be removed in a future release. The HoltWinters operator is a forecasting operator, which uses the Holt-Winters algorithm to do long-term forecasting.
HoltWinters2: The HoltWinters2 operator is a forecasting operator, which uses the Holt-Winters algorithm to do long-term forecasting.
HostProfiling: The HostProfiling operator analyzes DNS response traffic and reports whether or not the behaviour of the hosts are suspicious.
Import: The Import operator receives tuples from streams that are made available by Export operators of applications that are running in the same streaming middleware instance.
IncrementalInterpolate: The IncrementalInterpolate operator calculates missing values in a time series.
InetSource: The InetSource operator periodically retrieves text-based data from remote locations on an internet or intranet network and generates a stream from those contents.
JMSSink: The JMSSink operator creates messages from InfoSphere Streams tuples and writes the messages to a WebSphere® MQ or an Apache Active MQ queue or topic.
JMSSource: The JMSSource operator reads data from a WebSphere MQ or an Apache Active MQ queue or a topic and creates tuples from the read data.
JavaOp: The JavaOp operator is used to call out to operators implemented in Java™ by using the Java Operator API.
JobControlPlane: The JobControlPlane composite operator must be added to any application with a consistent region.
Join: The Join operator is used to correlate tuples from two streams that are based on user-specified match predicates and window configurations.
KMeansClustering: Cluster analysis is a popular technique used to find natural grouping of a set of objects.
KafkaConsumer: This operator acts as a Kafka consumer receiving messages for a single topic.
KafkaProducer: This operator acts as a Kafka producer sending tuples as messages to a Kafka broker.
Kalman: The Kalman operator runs an adaptive filter on a time series and can used for tracking, smoothing, adaptation.
LPC: The Linear Predictive Coding (LPC) operator uses an autoregressive (AR) model to predict values in a time series.
MQTTSink: The MQTTSink operator creates a message for every tuple it receives on its input port and publishes the message to an MQTT server.
MQTTSource: The MQTTSource operator subscribes to MQTT topics and receives messages when they are published to subscribed topics.
MatchRegex: The MatchRegex operator matches a regular expression pattern over the sequence of input tuples to detect composite events.
MetricsSink: The MetricsSink operator reads tuples and populates metrics with the values.
NetezzaLoad: The NetezzaLoad operator performs high speed loads into a Netezza® database.
NetezzaPrepareLoad: The NetezzaPrepareLoad operator converts an incoming tuple to a delimited string, which can be written to Netezza with its external table interface.
Normalize: The Normalize operator incrementally estimates the means and variance and can normalize the time series to zero means and unit variance.
ODBCAppend: The ODBCAppend operator stores an input stream into a database management system table.
ODBCEnrich: The ODBCEnrich operator generates a stream from an input tuple and the result set of an SQL SELECT statement.
ODBCRun: The ODBCRun operator runs a user-defined SQL statement that is based on an input tuple.
ODBCSource: The ODBCSource operator generates an output stream from the result set of an SQL SELECT statement.
ODMRulesetExecutor: The ODMRulesetExecutor operator creates input ruleset parameters from IBM InfoSphere Streams tuples and converts the output ruleset parameters that are generated by the ODM Rules Execution Server to tuples.
OSMCorrelator: The OSMCorrelator correlates information read by the OSMXMLGeometrySource to map generated edge IDs back to the original Way ID from the OpenStreetMaps map (.osm file).
OSMPointMatcher: The OSMPointMapMatcher composite analyzes time based object location data to heuristically project points on a network of roads specified by an OpenStreetMaps XML map file.
OSMXMLGeometrySource: OSMXMLGeometrySource reads in an OSM XML map file (.osm file) and generates geometry tuples for consumption by the PointMapMatcher and PathMapMatcher operators.
OpportunityRater: The OpportunityRater operator uses use a fairly simple analytic for identifying opportunities.
PSAX: The Piecewise and Aggregate operator, PSAX provides a symbolic representation of a real-valued time series data by transforming an input time series into an intermediate Piecewise Aggregate Approximation (PAA) representation and symbolizing the PAA representation into a discrete string.
Pair: The Pair operator is used to pair tuples from two or more streams.
Parse: The Parse operator is similar to the FileSource, TCPSource, and UDPSource operators, in that it transforms input data in a raw form into well-structured SPL tuples.
PointMapMatcher: The PointMapMatcher operator analyzes time based object location data to heuristically project points on a network of edges, as the original data may be imprecise.
PredictiveBlacklisting: The PredictiveBlacklisting operator analyzes the feature vector produced by the PredictiveBlacklistingFE operator using an SPSS® model.
PredictiveBlacklistingFE: The PredictiveBlacklistingFE operator ingests DNS response traffic and outputs a feature vector that is used by the PredictiveBlacklisting operator.
Publish: Publish a stream to a topic.
Punctor: The Punctor operator is used to transform input tuples into output ones and add window punctuation to the output.
RLSFilter: The Recursive Least Squares (RLS) is linear regression estimation algorithm that learns to predict a target time series, given inputs.
RScript: The RScript operator maps input tuple attributes to objects that can be used in R commands.
ReSample: The ReSample operator changes the sampling rate of a time series.
Regression: The Regression operator calculates the predicted value and the predicted standard deviation for each tuple in the input stream and automatically assigns those values to output stream attributes.
ReplayableStart: The ReplayableStart operator forwards tuples and punctuations from its input port to its output port.
STD: The seasonal trend decomposition (STD) operator transforms an input time series into three time series that represent the season, the trend, and the residuals.
ScheduledBeacon: The ScheduledBeacon operator is a utility source that generates tuples on-the-ﬂy.
Sort: The Sort operator is used to order tuples that are based on user-specified ordering expressions and window configurations.
SparkClusteringKMeans: This operator provides support for analysis of incoming tuple data against Apache Spark's kmeans clustering machine learning library.
SparkCollaborativeFilteringALS: This operator provides support for analysis of incoming tuple data against Apache Spark's collaborative filtering machine learning library.
SparkDecisionTree: This operator provides support for analysis of incoming tuple data against Apache Spark's decision tree machine learning library.
SparkEnsembleGradientBoostedTrees: This operator provides support for analysis of incoming tuple data against Apache Spark's decision tree ensembles machine learning library.
SparkEnsembleRandomForest: This operator provides support for analysis of incoming tuple data against Apache Spark's decision tree ensembles machine learning library.
SparkIsotonicRegression: This operator provides support for analysis of incoming tuple data against Apache Spark's isotonic regression machine learning library.
SparkLinearRegression: This operator provides support for analysis of incoming tuple data against Apache Spark's linear regression machine learning library.
SparkLinearSVM: This operator provides support for analysis of incoming tuple data against Apache Spark's SVM machine learning library.
SparkLogisticRegression: This operator provides support for analysis of incoming tuple data against Apache Spark's logistic regression machine learning library.
SparkNaiveBayes: This operator provides support for analysis of incoming tuple data against Apache Spark's naive bayes machine learning library.
SpatialGridIndex: The SpatialGridIndex operator stores objects and their location.
SpatialRouter: The SpatialRouter operator is used to split an input stream that contains geographical data into two or more output streams, based on the geographic location specified by each tuple.
Split: The Split operator is used to split a stream into one or more output streams, which are based on a user-specified split condition.
StreamToFIXMessage: The StreamToFixMessage operator takes a stream of attributes and converts it to a valid Financial Information eXchange (FIX) message.
StructureParse: The StructureParse operator parses a binary data stream, which contains fixed-size structures; therefore, the data is passed in using a blob attribute.
Subscribe: Subscribe to a topic.
Switch: The Switch operator is used to temporarily stop tuples from flowing.
TCPSink: The TCPSink operator writes data to a TCP socket in the form of tuples.
TCPSource: The TCPSource operator reads data from a TCP socket and creates tuples out of it.
TSWindowing: The TSWindowing operator can be used to isolate a portion of the signal in a specified duration.
TextExtract: The TextExtract operator facilitates the use of the Text Analytics component of IBM InfoSphere BigInsights® in IBM InfoSphere Streams.
ThreadedSplit: The ThreadedSplit operator splits tuples across multiple output ports to improve concurrency.
Throttle: The Throttle operator is used to pace a stream to make it flow at a specified rate.
TrailingPriceStatsCalculator: The TrailingPriceStatsCalculator operator computes the volume-weighted average price (VWAP) of the equities streamed into it, each over a range of the three most-recent trading prices for that equity.
UDPSink: The UDPSink operator writes data to a UDP socket in the form of tuples (and punctuation).
UDPSource: The UDPSource operator reads data from a UDP socket and creates tuples and punctuation out of it.
Union: The Union operator merges the streams that are connected to multiple input ports into a single stream.
V1TCPSink: The V1TCPSink operator writes binary data to a TCP socket that is connected to an InfoSphere Streams Version 1.2 TCP Source operator. It can be configured as a TCP server, which listens for a client connection, or as a TCP client, which initiates a connection to a server.
V1TCPSource: The V1TCPSource operator reads binary data from a TCP socket that is connected to a InfoSphere Streams Version 1.2 TCP Sink operator and creates tuples from that data.
VAR: DEPRECATED: The com.ibm.streams.timeseries.modeling.VAR operator is deprecated and is replaced by the com.ibm.streams.timeseries.modeling.VAR2 operator. The deprecated operator might be removed in a future release.
VAR2: The VAR2 operator tracks data movement and predicts the next expected time series by using a multivariate autoregressive model.
VWAPDeltaAggressive: The VWAPDeltaAggressive operator examines the opportunity levels that are coming in from the OpportunityRater operator.
VWAPDeltaConservative: The VWAPDeltaConservative operator examines the opportunity levels that are coming in from the OpportunityRater operator.
XMLParse: The XMLParse operator accepts a single input stream and generates tuples as a result.
XMSSink: The XMSSink operator takes messages from IBM InfoSphere Streams and can send them to a WebSphere MQ queue or topic.
XMSSource: The XMSSource operator reads data from a WebSphere MQ queue or topic and creates tuples out of it.