Troubleshooting - Aster Analytics
Teradata Aster Analytics Foundation User Guide
Product
Aster Analytics
Release Number
6.21
Published
November 2016
Language
English (United States)
Last Update
2018-04-14
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Product Category
Software
Preface
Overview
Conventions Used in This Guide
Typefaces
Notation Conventions
Command Shell Text Conventions
Contact Teradata Global Technical Support (GTS)
About Teradata Aster
About This Document
Version History
Introduction
Introduction
Analytics at Scale: Full Data Set Analysis
Introduction to Teradata Aster SQL-MapReduce
MapReduce
Aster Database SQL-MapReduce
SQL-MapReduce Query Syntax
SQL-MapReduce with Multiple Inputs
Benefits of Multiple-Input Functions
How Multiple Inputs are Processed
Types of SQL-MapReduce Inputs
Semantic Requirements for SQL-MapReduce Functions
Allowed Multiple-Input Structures
Rules for Number of Inputs by Type
Rules for Table Aliases
Number of Inputs
Use Cases and Examples for Multiple Inputs
Cogroup Use Case
Cogroup Example
Dimensional Input Use Case: Lookup Tables
Dimensional Input Example
Dimensional Input Use Case: Machine Learning
SQL-MapReduce Multiple Input FAQ
How are multiple inputs combined?
Can dimensional inputs include non-deterministic expressions?
Where will the output of the function be located?
Aster Analytics Function Product Bundles
Aster Analytics Functions by Product Bundle
Premium Path
Premium Relationship
Analytics Foundation
Premium Graph
Aster Analytics
Aster Scoring SDK
Aster Analytics Functions by Category
Time Series, Path, and Attribution Analysis
Pattern Matching with Teradata Aster nPath
Statistical Analysis
Text Analysis
Cluster Analysis
Naive Bayes
Ensemble Methods
Association Analysis
Graph Analysis
Aster Scoring SDK
NeuralNet
Data Transformation
Aster Database Utilities
Installing Aster Analytics Functions
Installing Aster Analytics Functions
Aster Analytics Function Version Numbers
Finding Function Version Numbers
Aster Analytics Compatibility Matrix
Aster Analytics Function Packages
Downloading an Aster Analytics Function Package
Install and Uninstall Scripts
Scripts for the Schema PUBLIC
Getting Uninstall Scripts for Releases AA 6.0 and Later
Getting Scripts for a Specified Schema
Installing an Aster Analytics Function Package
Set Default Schema for Function Users
Setting Permissions to Allow Users to Run Functions
Set Additional Permissions If Functions Are Not on PUBLIC
Testing the Functions
Updating an Aster Analytics Function Package
Installing a Function in a Specific Schema
Managing Files with ACT Commands
Usage Notes
Enclosing Database Object Names in Double Quotation Marks
Boolean Argument Values
Column Specification Arguments
DATE Columns
BC/BCE Timestamps
Creating a Timestamp Column
CREATE Privileges
Add Model File Locations to the Default Search Path
Database Connections with Authentication Cascading
Using Authentication Cascading
Authentication Argument Syntax
Arguments
Example
Connecting to Aster Database Using SSL JDBC Connections
Arguments
Example
Error Message Delays
Sparse Tables and Dense Tables
Permanent Tables as Output of Driver-Based Functions
Input Table Aliases
Time Series, Path, and Attribution Analysis
Time Series, Path, and Attribution Analysis
Arima
Summary
Background
Nonseasonal ARIMA Model
Seasonal ARIMA Model
Usage
Arima Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
ArimaPredictor
Summary
Usage
ArimaPredictor Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Attribution
Summary
Background
Attribution (Multiple-Input Version)
Summary
Usage
Attribution Syntax (Multiple Inputs)
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Attribution (Single-Input Version)
Summary
Usage
Attribution Syntax (Single Input)
Arguments
Input
Output
Examples
Example 1: One Regular Model, Multiple Optional Models
Input
SQL-MapReduce Call
Output
Example 2: Multiple Regular Models, One Optional Model
Input
SQL-MapReduce Call
Output
Single-Input Attribution Example 3: Dynamic Weighted Distribution Models
Input
SQL-MapReduce Call
Output
Single-Input Attribution Example 4: Window Models
Input
SQL-MapReduce Call
Output
Single-Input Attribution Example 5: Single-Window Model
Input
SQL-MapReduce Call
Output
Single-Input Attribution Example 6: Unused Segment Windows
Input
SQL-MapReduce Call
Output
Burst
Summary
Usage
Burst Syntax
Arguments
Input
Output
Examples
Example 1: Time_Interval Argument
Input
SQL-MapReduce Call
Output
Example 2: Time_Table Argument
Input
SQL-MapReduce Call
Output
Change-Point Detection Functions
Summary
Background
Retrospective Change-Point Detection
Real-Time Change-Point Detection
ChangePointDetection
Summary
Usage
ChangePointDetection Syntax
Arguments
Input
Output
Examples
Example 1: Two Series, Default Options
Input
SQL-MapReduce Call
Output
Example 2: One Series, Default Options
Input
SQL-MapReduce Call
Output
Example 3: One Series, VERBOSE Output
Input
SQL-MapReduce Call
Output
Example 4: One Series, Penalty 10
Input
SQL-MapReduce Call
Output
Example 5: One Series, SEGMENT Output, Penalty 10
Input
SQL-MapReduce Call
Output
Example 6: One Series, Penalty 20, Linear Regression
Input
SQL-MapReduce Call
Output
RtChangePointDetection
Summary
Usage
RtChangePointDetection Syntax
Arguments
Input
Output
Examples
Example 1: Threshold 10, Window Size 3, Default Output
Input
SQL-MapReduce Call
Output
Example 2: Threshold 20, Window Size 3, VERBOSE Output
Input
SQL-MapReduce Call
Output
Example 3: Threshold 100, Window Size 3, Default Output
Input
SQL-MapReduce Call
Output
Convergent Cross-Mapping
CCMPrepare
Usage
CCMPrepare Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
CCM
Summary
Usage
CCM Syntax
Arguments
Input
Output
Examples
Example 1: Numeric Causes and Effects with Default Values
Input
SQL-MapReduce Call
Output
Example 2: Mixed Categorical and Numeric Causes and Effects
Input
SQL-MapReduce Call
Output
DTW
Summary
Usage
DTW Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
DWT
Summary
Background
Usage
DWT Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
DWT2D
Summary
Background
Usage
DWT2D Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
FrequentPaths
Summary
Background
Usage
FrequentPaths Syntax
Arguments
Input
Output
Examples
Example 1: ItemColumn Argument Specified
Input
SQL-MapReduce Call
Output
Example 2: ItemDefinition Argument Specified
Input
SQL-MapReduce Call
Output
Example 3: GroupByColumns Argument Specified
Input
SQL-MapReduce Call
Output
Example 4: SEQUENCEPATTERNRELATION Argument Specified
Input
SQL-MapReduce Call
Output
Example 5: PathFilters Argument Specified
Input
SQL-MapReduce Call
Output
Example 6: Output Only Closed Patterns
Input
SQL-MapReduce Call
Output
Example 7: Using nPath and FrequentPaths to Select Sequences
Input
Create the FrequentPaths Input Table
SQL-MapReduce Call
Output
IDWT
Summary
Usage
IDWT Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
IDWT2D
Summary
Usage
IDWT2D Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Interpolator
Summary
Usage
Interpolator Syntax
Arguments
Input
Output
Examples
Input
Example 1: Aggregation
SQL-MapReduce Call
Output
Example 2: Constant Interpolation
SQL-MapReduce Call
Output
Example 3: Linear Interpolation
SQL-MapReduce Call
Output
Example 4: Median Interpolation
SQL-MapReduce Call
Output
Example 5: Spline Interpolation
SQL-MapReduce Call
Output
Example 6: Loess Interpolation
SQL-MapReduce Call
Output
Path Analysis Functions
Summary
Path_Generator
Summary
Usage
Path_Generator Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Path_Summarizer
Summary
Usage
Path_Summarizer Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Path_Start
Summary
Usage
Path_Start Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Path_Analyzer
Summary
Usage
Path_Analyzer Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
SAX2
Summary
Background
Usage
SAX2 Syntax (Single Input)
SAX2 Syntax (Multiple Inputs)
Arguments
Input
Output
Examples
Input
Example 1: Global Window, Default Output
SQL-MapReduce Call
Output
Example 2: Sliding Window, Default Output
SQL-MapReduce Call
Output
Example 3: Sliding Window, Bitmap Output
SQL-MapReduce Call
Output
Example 4: Sliding Window, Character Output
SQL-MapReduce Call
Output
Example 5: Multiple-Input Version
SQL-MapReduce Call
Output
SeriesSplitter
Summary
Background
Usage
SeriesSplitter Syntax
Arguments
Input
Output
Examples
Input
Example 1: Partition Splitter
SQL-MapReduce Call
Output
Example 2: Using SeriesSplitter with Interpolator
SQL-MapReduce Calls
Troubleshooting
Sessionize
Summary
Background
Usage
Sessionize Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Shapelet Functions
Overview
UnsupervisedShapelet
Summary
Usage
UnsupervisedShapelet Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Troubleshooting
Problem: The function runs slowly for large input data sets.
Workarounds:
Problem: Clustering accuracy is not good enough.
Workarounds:
SupervisedShapeletTrainer
Summary
Usage
SupervisedShapeletTrainer Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Troubleshooting
Problem: The function runs slowly for large input data sets.
Workarounds:
Problem: Classification accuracy is not good enough.
Workarounds:
SupervisedShapeletClassifier
Summary
Usage
SupervisedShapeletClassifier Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
VARMAX
Summary
Usage
VARMAX Syntax
Arguments
Input
Output
Examples
Input
Example 1: VARMAX without Exogenous Model
SQL-MapReduce Call
Output
Example 2: VARMAX with Exogenous Model
SQL-MapReduce Call
Output
Example 3: VARMAX with Seasonal Model and without Exogenous Model
SQL-MapReduce Call
Output
Example 4: VARMAX with All Models
SQL-MapReduce Call
Output
Pattern Matching with Teradata Aster nPath
Pattern Matching with Teradata Aster nPath
nPath
Summary
Usage
nPath Syntax
Arguments
Range-Matching Feature
Input
Output
Patterns
Greedy Pattern Matching
Symbols
LAG and LEAD Expressions in Symbol Predicates
LAG Expression Syntax
LAG and LEAD Expression Rules
LAG and LEAD Expressions Example 1
Input
SQL-MapReduce Call
Output
LAG and LEAD Expressions Example 2
Input
SQL-MapReduce Call
Output
Filters
Example
Input
SQL-MapReduce Call
Output
Results
Example 1
Input
SQL-MapReduce Call
Output
Example 2
Input
SQL-MapReduce Call
Output
Example 3
Input
SQL-MapReduce Call
Output
nPath Examples
Clickstream Data Examples
Input, Symbols, and Symbol Predicates
Basic SQL-MapReduce Call Structure
Combining Values from Adjacent Rows
Counting Preceding Rows in a Sequence
Complex Path Query
Range-Matching Examples
Input
Example 1: Accumulate Pages Visited in Each Session
SQL-MapReduce Call
Output
Example 2: Find Sessions That Start at Home Page and Visit Page1
SQL-MapReduce Call
Output
Example 3: Find Paths to Checkout Page for Purchases Over $200
SQL-MapReduce Call
Output
Example 4: Use OVERLAPPING Mode
SQL-MapReduce Call
Output
Example 5: Find First Product with Multiple Referrers in Any Session
SQL-MapReduce Call
Output
Example 6: Find Data for Sessions that Checked 3-6 Products
SQL-MapReduce Call
Output
Example 7: Find Data for Sessions that Checked at Least 3 Products
SQL-MapReduce Call
Output
Multiple Partitioned Input Tables
Input
SQL-MapReduce Call
Multiple Partitioned Input Tables and Dimension Input Table
Input
SQL-MapReduce Call
Output
Statistical Analysis
Statistical Analysis
Approximate Distinct Count
Summary
Background
Usage
Approximate Distinct Count Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Approximate Percentile
Summary
Background
Usage
Approximate Percentile Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
CMAVG
Summary
Background
Usage
CMAVG Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
ConfusionMatrix
Summary
Background
Usage
ConfusionMatrix Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Correlation
Summary
Usage
Correlation Syntax
Arguments
Input
Output
Examples
Input
Example 1: Including PARTITION BY Clause
SQL-MapReduce Call
Output
Example 2: Omitting PARTITION BY Clause
SQL-MapReduce Call
Output
CoxPH
Summary
Background
Usage
CoxPH Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
CoxPredict
Summary
Background
Usage
CoxPredict Syntax
Arguments
Input
Output
Examples
Input
Example 1: No Reference Values Provided
SQL-MapReduce Call
Output
Example 2: Partition by Name/ID and No Reference Values
SQL-MapReduce Call
Output
Example 3: Use Reference Values
SQL-MapReduce Call
Output
Example 4: Use Reference values and Partition by id
SQL-MapReduce Call
Output
Example 5: Use Units Values
SQL-MapReduce Call
Output
Hypothesis-Test Mode
Summary
Usage
Hypothesis-Test Mode Syntax (Continuous Distributions)
Option 1: For Multiple-Node Data Sets
Option 2: For Single-Node Data Sets
Hypothesis-Test Mode Syntax (Discrete Distributions)
Option 1: For Multiple-Node Data Sets
Option 2: For Single-Node Data Sets and Any CvM Test
Arguments
Input
Output
Results (statistics and p-values)
Examples
Example 1: Normality Tests without 'groupingColumns'
Input
SQL-MapReduce Call
Output
Example 2: Normality Tests with 'groupingColumns'
Input
SQL-MapReduce Call
Output
CoxSurvFit
Summary
Background
Usage
CoxSurvFit Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
CrossValidation
Summary
Usage
CrossValidation Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Distribution Matching
Summary
Best-Match Mode
Summary
Usage
Best-Match Mode Syntax (DOUBLE PRECISION Input)
Best-Match Mode Syntax (INTEGER Input)
Arguments
Input
Output
Examples
Example 1: Input Values of Type DOUBLE PRECISION
Input
SQL-MapReduce Call
Output
Example 2: Input Values of Type INTEGER
Input
SQL-MapReduce Call
Output
EMAVG
Summary
Background
Usage
EMAVG Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
FMeasure
Summary
Background
Usage
FMeasure Syntax
Arguments
Input
Output
Examples
Input
Example 1: Output All Classes
SQL-MapReduce Call
Output
Example 2: Output Specified Classes
SQL-MapReduce Call
Output
GLM
Summary
Background
Usage
GLM Syntax
Arguments
Input
Onscreen Output
Columns
Rows
Output Table
Odds Ratio and Confidence Intervals
Goodness-of-Fit Tests
Deviance
Wald Test
Rao's Score Test
Pearson’s Chi-squared Statistic
Examples
Example 1: Logistic Regression Analysis with Intercept
Input
SQL-MapReduce Call
Output
Example 2: Logistic Regression Analysis with Step Argument
Input
SQL-MapReduce Call
Output
Example 3: Gaussian Distribution Analysis with Default Options
Input
SQL-MapReduce Call
Output
GLMPredict
Summary
Usage
GLMPredict Syntax
Arguments
Input
Output
Examples
Example 1: Logistic Distribution Prediction
Input
SQL-MapReduce Call
Output
Categorizing Column fitted_value
Prediction Accuracy
Example 2: Gaussian Distribution Prediction
Input
SQL-MapReduce Call
Output
RMSE
Hidden Markov Model Functions
Overview of Hidden Markov Model
Models and Descriptions
Aster Distributed Platforms
HMMUnsupervisedLearner
Summary
Usage
HMMUnsupervisedLearner Syntax
Arguments
Input
Output
Example
Loan Default Prediction
Input
SQL-MapReduce Call
Output
HMMSupervisedLearner
Summary
Usage
HMMSupervisedLearner Syntax
Arguments
Input
Output
Example
Customer Loyalty Prediction
Input
SQL-MapReduce Call
Output
HMMEvaluator
Summary
Usage
HMMEvaluator Syntax
Arguments
Input
Output
Example
Loan Default Prediction (from HMMUnsupervisedLearner)
Input
SQL-MapReduce Call
Output
HMMDecoder
Summary
Usage
HMMDecoder Syntax
Arguments
Input
Output
Examples
Example 1: Loan Default Prediction (from Unsupervised Learner)
Input
SQL-MapReduce Call
Output
Example 2: Customer Loyalty Prediction (from Supervised Learner)
Input
SQL-MapReduce Call
Output
Example 3: Part-of-Speech Tagging
Input
SQL-MapReduce Call
Output
Example 4: Bank Customer Churn
Input
SQL-MapReduce Call
Output
Histogram
Summary
Background
Sturges' Algorithm
Scott's Algorithm
Usage
Histogram (Hist) Syntax
Arguments
Input
Output
Examples
Input
Example 1: Bins with Sturges Algorithm
SQL-MapReduce Call
Output
Example 2: Bins with Scott Algorithm
SQL-MapReduce Call
Output
Example 3: You Specify Bins
SQL-MapReduce Call
Output
KNN
Summary
Background
Usage
KNN Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
User-Defined Distance Metric
LARS Functions
Summary
Background
LARS
Summary
Usage
LARS Syntax
Arguments
Input
Output
Interpreting the Output
Examples
Input
Example 1: Method ('lar')
SQL-MapReduce Call
Output
Example 2: Method ('lasso')
SQL-MapReduce Call
Output
LARSPredict
Summary
Usage
LARSPredict Syntax
Arguments
Input
Output
Examples
Example 1: Model ('diabetes_lars')
Input
SQL-MapReduce Call
Output
Example 2: Model ('diabetes_lasso')
Input
SQL-MapReduce Call
Output
Linear Regression
Summary
Background
Usage
Linear Regression Syntax
Input
Output
Example
Input
SQL-MapReduce Call
Output
LRTEST
Summary
Background
Usage
LRTEST Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call 1 - Create model based on temp variable
Output
SQL-MapReduce Call 2 - Create null model
Output
SQL-MapReduce Call 3 - LRTEST
Output
Percentile
Summary
Usage
Percentile Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Principal Component Analysis
Summary
Background
Usage
Principal Component Analysis (PCA) Syntax
Arguments
Input
Output
Example
Input
SQL to Create Table of Eigenvectors
Output (Table of Eigenvectors)
SQL to Create Table of Principal Components
Output (Table of Principal Components)
SQL to Create View of Correlations
Output (View of Correlations)
SQL-MapReduce Call to Get pca_1 Correlation Coefficients
Output (pca_1 Correlation Coefficients)
SQL-MapReduce Call to Get pca_2 Correlation Coefficients
Output (pca_2 Correlation Coefficients)
SQL-MapReduce Call to Get pca_3 Correlation Coefficients
Output (pca_3 Correlation Coefficients)
Summary
PCAPlot
Summary
Usage
PCAPlot Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
RandomSample
Summary
Usage
RandomSample Syntax
Arguments
Input
Output
Examples
Input
Example 1: Basic Sampling (Weighted)
SQL-MapReduce Call
Output
Example 2: KMeans++ Sampling
SQL-MapReduce Call
Output
Example 3: KMeans|| Sampling
Create and Populate Input Table
SQL-MapReduce Call
Output
Sample
Summary
Usage
Sample Syntax
Unconditional Sampling, Single Sample Rate
Unconditional Sampling, Approximate Sample Size
Conditional Simple Sampling, Single Sample Rate
Conditional Sampling, Variable Sample Rates
Conditional Sampling, Approximate Sample Size
Conditional Sampling, Variable Approximate Sample Sizes
Arguments
Input
Output
Examples
Input
Example 1: Unconditional Sampling with Single Sample Rate
SQL-MapReduce Call
Output
Example 2: Conditional Sampling with Variable Sample Rate
SQL-MapReduce Call
Output
Example 3: Unconditional Sampling with Total (Single) Approximate SampleSize
SQL-MapReduce Call
Output
Example 4: Conditional Sampling with Variable Approximate SampleSize
SQL-MapReduce Call
Output
Shapley Value Functions
Summary
Background
GenerateCombination
Usage
GenerateCombination Syntax
Input
Output
Examples
SortCombination
Usage
SortCombination Syntax
Arguments
Input
Output
Examples
AddOnePlayer
Usage
AddOnePlayer Syntax
Arguments
Input
Output
SQL Statements to Compute the Shapley Value
Examples
Example 1: Use GenerateCombination and AddOnePlayer
Input
Generate Payoff Tables for Each Combination
SQL-MapReduce Call
Output
Add One Player to Each Combination
SQL-MapReduce Call
Output
Compute Shapley Values
SQL-MapReduce Call
Output
Example 2: Use nPath to Create Input to GenerateCombination
Input
Generate and Load Click-Stream Sequences
Output
Use nPath to Generate Conversion Counts
Output
Use nPath to Generate Total Counts
Output
Compute Shapley Values
Output
Compute Augmented Characteristic Values Table (ACVS)
Output
Compute Unnormalized Shapley Values from CVS and ACVS Table
Output
SMAVG
Summary
Background
Usage
SMAVG Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Support Vector Machine (SVM) Functions
SparseSVM Functions
SparseSVMTrainer
Summary
Usage
SparseSVMTrainer Syntax
Arguments
Input
Output
Example
Input
Create Input Table in Sparse Format
Create Training and Testing Tables
SQL-MapReduce Call
Output
SparseSVMPredictor
Summary
Usage
SparseSVMPredictor Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Check Prediction Accuracy
SVMModelPrinter
Summary
Usage
SVMModelPrinter Syntax
Arguments
Input
Output
Examples
Example 1: ShowSummary('true')
SQL-MapReduce Call
Output
Example 2: ShowSummary('false')
SQL-MapReduce Call
Output
DenseSVM Functions
DenseSVMTrainer
Summary
Usage
DenseSVMTrainer Syntax
Arguments
Input
Output
Examples
Input
Train and Test Set
Example 1: Linear Model
SQL-MapReduce Call
Output
Example 2: Polynomial Model
SQL-MapReduce Call
Output
Example 3: Radial Basis Model (RBF) Model
SQL-MapReduce Call
Output
Example 4: Sigmoid Model
SQL-MapReduce Call
Output
DenseSVMPredictor
Summary
Usage
DenseSVMPredictor Syntax
Arguments
Input
Output
Examples
Input
Example 1: Linear Model
SQL-MapReduce Call
Output
Example 2: Polynomial Model
SQL-MapReduce Call
Output
Example 3: Radial Basis Model (RBF) Model
SQL-MapReduce Call
Output
Example 4: Sigmoid Model
SQL-MapReduce Call
Output
DenseSVMModelPrinter
Summary
Usage
DenseSVMModelPrinter Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call with ShowSummary('false')
Output
SQL-MapReduce Call with ShowSummary('true')
Output
VectorDistance
Summary
Background
Cosine Similarity
Euclidean Distance
Manhattan Distance
Binary Distance
Usage
VectorDistance Syntax
Arguments
Input
Output
Examples
Input
Example 1: Default Thresholds
SQL-MapReduce Call
Output
Example 2: Specified Thresholds
SQL-MapReduce Call
Output
VWAP
Summary
Usage
VWAP Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
WMAVG
Summary
Background
Usage
WMAVG Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Text Analysis
Text Analysis
LDA Functions
Summary
Background
LDATrainer
Summary
Usage
LDATrainer Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
LDAInference
Summary
Usage
LDAInference Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
LDATopicPrinter
Summary
Usage
LDATopicPrinter Syntax
Arguments
Input
Output
Examples
Input
Example 1: ShowSummary ('true')
SQL-MapReduce Call
Output
Example 2: OutputByWord ('false')
SQL-MapReduce Call
Output
Example 3: ShowWordWeight('true') and ShowWordCount('true')
SQL-MapReduce Call
Output
Levenshtein Distance (LDist)
Summary
Usage
Levenshtein Distance (LDist) Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Naive Bayes Text Classifier
Summary
NaiveBayesTextClassifierTrainer
Summary
Usage
NaiveBayesTextClassifierTrainer Syntax
Arguments
Input
Output
Examples
English Example
Input
SQL Statement to Create Model Table
Output
Chinese Example
Input
SQL Statement to Create Model Table
Output
NaiveBayesTextClassifierPredict
Summary
Usage
NaiveBayesTextClassifierPredict Syntax
Arguments
Input
Output
Examples
English Example
Input
SQL-MapReduce Call
Output
Chinese Example
Input
SQL-MapReduce Call
Output
NER Functions (CRF Model Implementation)
Summary
NERTrainer
Summary
Usage
NERTrainer Syntax
Arguments
Feature Template
Part 1 of the Example Template File
Part 2 of the Example Template File
Input
Output
Example
Input
SQL-MapReduce Call
Output
NER
Summary
Usage
NER Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
NEREvaluator
Summary
Usage
NEREvaluator Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
NER Functions (Max Entropy Model Implementation)
Summary
FindNamedEntity
Summary
Usage
FindNamedEntity Syntax
Arguments
Creating the Table of Default Models
Input
Output
Example
Input
SQL-MapReduce Call
Output
TrainNamedEntityFinder
Summary
Usage
TrainNamedEntityFinder Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Evaluate Named Entity Finder
Summary
Usage
Evaluate Named Entity Finder Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
nGram
Summary
Background
Usage
nGram Syntax
Arguments
Input
Output
Examples
Input
Example 1: Overlapping ('true') and TotalGramCount ('true')
SQL-MapReduce Call
Output
Example 2: Overlapping ('false') and TotalGramCount ('false')
SQL-MapReduce Call
Output
POSTagger
Summary
Background
Usage
POSTagger Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Sentenizer
Summary
Background
Usage
Sentenizer Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Sentiment Extraction Functions
Summary
Background
TrainSentimentExtractor
Summary
Usage
TrainSentimentExtractor Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
ExtractSentiment
Summary
Usage
ExtractSentiment Syntax
Arguments
Input
Output
Examples
Prerequisites
Input
Example 1: Model ('dictionary'), Level ('document')
SQL-MapReduce Call
Output
Example 2: Model ('dictionary'), Level ('sentence')
SQL-MapReduce Call
Output
Example 3: Model ('classification:default_sentiment_classification_model.bin')
SQL-MapReduce Call
Output
Example 4: Model ('classification:sentimentmodel1.bin')
SQL-MapReduce Call
Output
Example 5: Dictionary Table Instead of Model File
SQL-MapReduce Call
Output
EvaluateSentimentExtractor
Summary
Usage
EvaluateSentimentExtractor Syntax
Arguments
Input
Output
Example
Input
Example 1: Model ('dictionary')
SQL-MapReduce Call
Output
Example 2: Model ('classification:default_sentiment_classification_model.bin')
SQL-MapReduce Call
Output
Example 3: Model ('classification:sentimentmodel1.bin')
SQL-MapReduce Call
Output
Example 4: Dictionary Table Instead of Model File
SQL-MapReduce Call
Output
Text Classifier
Summary
Background
TextClassifierTrainer
Summary
Usage
TextClassifierTrainer Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
TextClassifier
Summary
Usage
TextClassifier Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
TextClassifierEvaluator
Summary
Usage
TextClassifierEvaluator Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Text_Parser
Summary
Background
Usage
Text_Parser Syntax
Arguments
Input
Output
Examples
Example 1: With StopWords and without StemmingExceptions
Input
SQL-MapReduce Call
Output
Example 2: With StemmingExceptions and without StopWords
Input
SQL-MapReduce Call
Output
TextChunker
Summary
Background
Usage
TextChunker Syntax
Arguments
Input
Output
Example
Example 1: Using Output from POSTagger
Input
SQL-MapReduce Call
Output
Example 2. Using Output from Sentenizer and POSTagger
Input
SQL-MapReduce Call
Output
TextMorph
Summary
Background
Usage
TextMorph Syntax
Arguments
Input
Output
Examples
Input
Example 1: SingleOutput ('true')
SQL-MapReduce Call
Output
Example 2: SingleOutput ('false')
SQL-MapReduce Call
Output
Example 3: POS ('noun', 'verb') and SingleOutput ('false')
SQL-MapReduce Call
Output
Example 4: POS ('noun', 'verb') and SingleOutput ('true')
SQL-MapReduce Call
Output
Example 5: Using TextMorph with POSTagger and TextTagging
POSTagger Input
Statement to Create POSTagger Output Table
POSTagger Output and TextMorph Input
Statement to Create TextMorph Output Table
TextMorph Output and TextTagging Input
SQL-MapReduce Call to TextTagging
TextTagging Output
TextTagging
Summary
Usage
TextTagging Syntax
Arguments
Defining Tagging Rules
Input
Output
Examples
Input
Example 1: Specify Rules Argument
SQL-MapReduce Call
Output
Example 2: Specify Rules Table
SQL-MapReduce Call
Output
Example 3: Specify Dictionary File in Rules Argument
SQL-MapReduce Call
Output
Example 4: Specify Superdist in Rules Argument
SQL-MapReduce Call
Output
TextTokenizer
Summary
Usage
TextTokenizer Syntax
Arguments
Input
Output
Examples
Example 1: Chinese Tokenization
Input
SQL-MapReduce Call 1
Output
SQL-MapReduce Call 2
Output
Example 2: Japanese Tokenization
Input
SQL-MapReduce Call 1
Output
SQL-MapReduce Call 2
Output
Example 3: English Tokenization
Input
SQL-MapReduce Call
Output
TF_IDF
Summary
Background
Usage
TF_IDF Syntax
Arguments
Input
Output
Examples
Example 1: TF_IDF on Tokenized Training Document Set
Input
Step 1: Create Tokenized Training Document Set
Step 2: Create Input for TF_IDF Function
SQL-MapReduce Call
Output
Example 2: TF_IDF on Tokenized Test Set
Input
Step 1. Create Tokenized Test Document Set
Step 2. Create Input for TF_IDF Function
SQL-MapReduce Call
Output
Cluster Analysis
Cluster Analysis
Canopy
Summary
Background
Usage
Canopy Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Gaussian Mixture Model Functions
GMMFit
Summary
Usage
GMMFit Syntax
Arguments
Input
Output
Examples
Input
Split Input into Training and Testing Data Sets
Example 1: Basic GMM, Spherical Covariance, Packed Output
Input
SQL-MapReduce Call
Output
Example 2: Basic GMM, Diagonal Covariance, Unpacked Output
SQL-MapReduce Call
Output
Example 3: DP-GMM, Full Covariance, Unpacked Output
SQL-MapReduce Call
Output
GMMPredict
Summary
Usage
GMMPredict Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
GMMProfile
Summary
Usage
GMMProfile Syntax
Input
Output
Examples
Example 1
Input
SQL-MapReduce Call
Output
Example 2
Input
SQL-MapReduce Call
Output
Example 3
Input
SQL-MapReduce Call
Output
KMeans
Summary
Background
Usage
KMeans Syntax
Arguments
Input
Output
Examples
Input
Example 1: NumClusters and UnpackColumns('false') by Default
SQL-MapReduce Call
Output
Example 2: NumClusters and UnpackColumns('true')
SQL-MapReduce Call
Output
Example 3: InitialSeeds and ClusteredOutput
SQL-MapReduce Call
Output
Example 4: CentroidsTable and ClusteredOutput
SQL-MapReduce Call
Output
KMeansPlot
Summary
Usage
KMeansPlot Syntax
Arguments
Input
Output
Example
Input
SQL-MapReference Call
Output
KModes
Summary
Usage
KModes Syntax
Arguments
Input
Output
Examples
Input
Example 1: Using InitialSeedTable
SQL-MapReduce Call
Output
Example 2: Using NumClusters
SQL-MapReduce Call
Output
KModesPredict
Summary
Usage
KModesPredict Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Minhash
Summary
Background
Usage
Minhash Syntax
Arguments
Example
Input
SQL-MapReduce Call
Output
Naive Bayes
Naive Bayes
Overview of Naive Bayes
Naive Bayes Functions
Summary
NaiveBayesMap and NaiveBayesReduce
Summary
Usage
Naive Bayes Syntax
Arguments
Input
Output
Naive Bayes Example
NaiveBayesMap Input: Training Table
Split Input into Training and Testing Data Sets
SQL-MapReduce Call to Generate the Model
NaiveBayesReduce and NaiveBayesMap Output: Model Table
NaiveBayesPredict Input
SQL-MapReduce Call to Predict Outcomes of Test Table Data
NaiveBayesPredict Output: Predict Outcomes Table
Prediction Accuracy
NaiveBayesPredict
Summary
Usage
NaiveBayesPredict Syntax
Arguments
Input
Output
Naive Bayes Example
NaiveBayesMap Input: Training Table
Split Input into Training and Testing Data Sets
SQL-MapReduce Call to Generate the Model
NaiveBayesReduce and NaiveBayesMap Output: Model Table
NaiveBayesPredict Input
SQL-MapReduce Call to Predict Outcomes of Test Table Data
NaiveBayesPredict Output: Predict Outcomes Table
Prediction Accuracy
Naive Bayes Example
NaiveBayesMap Input: Training Table
Split Input into Training and Testing Data Sets
SQL-MapReduce Call to Generate the Model
NaiveBayesReduce and NaiveBayesMap Output: Model Table
NaiveBayesPredict Input
SQL-MapReduce Call to Predict Outcomes of Test Table Data
NaiveBayesPredict Output: Predict Outcomes Table
Prediction Accuracy
Ensemble Methods
Ensemble Methods
Random Forest Functions
Summary
Background
Decision Tree Basics
Advantages of Decision Trees
Disadvantages of Decision Trees
Implementation Notes
Usage
Forest_Drive
Summary
Usage
Forest_Drive Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Forest_Predict
Summary
Usage
Forest_Predict Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Prediction Accuracy
Forest_Analyze
Summary
Usage
Forest_Analyze Syntax
Arguments
Input
Output
Examples
Input
Example 1
SQL-MapReduce Call
Output
Example 2: Calculating Variable importance
SQL-MapReduce Call
Output
Best Practices
Single Decision Tree Functions
Single_Tree_Drive
Summary
Background
Tree Building
Single_Tree_Drive Helper Functions
Difference between the Decision Tree Approaches
Usage
Single_Tree_Drive Syntax
Arguments
Input
Output
Examples
Example 1
Input
Split Input into Training and Testing Data Sets
Attribute Tables
Response Tables
SQL-MapReduce Call
Output
Example 2
Input
SQL-MapReduce Call
Output
Single_Tree_Predict
Summary
Usage
Single_Tree_Predict Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Prediction Accuracy
AdaBoost Functions
Background
AdaBoost_Drive
Summary
Usage
AdaBoost_Drive Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
AdaBoost_Predict
Summary
Usage
AdaBoost_Predict Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Prediction Accuracy
Association Analysis
Association Analysis
Basket_Generator
Summary
Background
Usage
Basket_Generator Syntax
Arguments
Input
Output
Examples
Input
Example 1: Partition by tranid
SQL-MapReduce Call
Output
Example 2: Increase BasketSize
SQL-MapReduce Call
Output
CFilter
Summary
Background
Usage
CFilter Syntax
Arguments
Input
Output
Deleting Duplicate Output Table Rows
Examples
Input
Example 1: Collaborative Filtering by Product
SQL-MapReduce Call
Output
Example 2: Collaborative Filtering by Customer Segment
SQL-MapReduce Call
Output
FPGrowth
Summary
Background
Usage
FPGrowth Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Recommender Functions
WSRecommender
Summary
Usage
WSRecommender Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
KNNRecommenderTrain
Summary
Usage
KNNRecommenderTrain Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
KNNRecommenderPredict
Summary
Usage
KNNRecommenderPredict Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Graph Analysis
Graph Analysis
Overview of Graph Analysis Functions
Graph Functions
Iterations
Graphs
Directed Graphs
Graph Discovery
AllPairsShortestPath
Summary
Usage
AllPairsShortestPath Syntax
Arguments
Input
Deleting Duplicate Edges Table Rows
Output
Examples
Input
Example 1: Unweighted, Unbounded Graph
SQL-MapReduce Call
Output
Example 2: Weighted, Unbounded Graph
SQL-MapReduce Call
Output
Example 3: Weighted, Bounded Graph with Sources
SQL-MapReduce Call
Output
Betweenness
Summary
Background
Usage
Betweenness Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Closeness
Summary
Background
Usage
Closeness Syntax
Arguments
Input
Output
Examples
Input
Example 1: Unweighted, Unbounded Graph
SQL-MapReduce Call
Output
Example 2: Weighted, Bounded Graph, MaxDistance=12
SQL-MapReduce Call
Output
Example 3: Weighted, Bounded Graph, MaxDistance=8
SQL-MapReduce Call
Output
EigenvectorCentrality
Summary
Background
Centrality Formulas
Eigenvector Centrality
Katz Centrality
Bonacich Centrality
Eigenvector and Eigenvalue
Power Iteration
Centrality Calculation
Usage
EigenvectorCentrality Syntax
Arguments
Input
Output
Examples
Input
Example 1: Eigenvector Centrality (by Default)
SQL-MapReduce Call
Output
Example 2: Katz Centrality
SQL-MapReduce Call
Output
Example 3: Bonacich Centrality
SQL-MapReduce Call
Output
gTree
Summary
Background
Usage
gTree Syntax
Arguments
Input
Output
Examples
Input
Example 1: Show All Paths from Root Nodes
SQL-GR Call
Output
Example 2: Show Only Paths That Cycle or End at Leaves
SQL-GR Call
Output
LocalClusteringCoefficient
Summary
Background
Unweighted, Undirected Network (BUN)
Unweighted, Directed Network (BDN)
Weighted, Directed Network (WDN)
Weighted, Undirected Network (WUN)
Usage
LocalClusteringCoefficient Syntax
Arguments
Input
Output
Examples
Input
Example 1: WUN
SQL-MapReduce Call
Output
Example 2: WUN with DegreeRange 3 or Greater
SQL-MapReduce Call
Output
Example 3: WDN
SQL-MapReduce Call
Output
LoopyBeliefPropagation
Summary
Background
Usage
LoopyBeliefPropagation Syntax
Arguments
Input
Output
Examples
Example 1: Equally Weighted Symptoms/Edges
Input
SQL-MapReduce Call
Output
Example 2: Unequally Weighted Symptoms/Edges
Input
SQL-MapReduce Call
Output
Modularity
Summary
Background
Definitions
Quality Metric
Resolution
Usage
Modularity Syntax
Arguments
Input
Output
Examples
Input
Example 1: Unweighted Edges
SQL-MapReduce Call
Output
Example 2: Weighted Edges and Community Edge Table
SQL-MapReduce Call
Output
Tips
Troubleshooting
nTree
Summary
Background
Equity Trading
Social Networking
Usage
nTree Syntax
Arguments
Cycles in nTree
Very Deep Trees
Input
Output
Examples
Example 1: Find an Employee’s Reports
Input
SQL-MapReduce Call
Output
Example 2: Find an Employee’s Management Chain
Input
SQL-MapReduce Call
Output
Example 3: Show Reporting Structure by Department
Input
SQL-MapReduce Call
Output
PageRank
Summary
Background
Usage
PageRank Syntax
Arguments
Input
Output
Example
SQL-MapReduce Call
Output
pSALSA
Summary
Background
SALSA
pSALSA
Usage
pSALSA Syntax
Arguments
Input
Output
Examples
Example 1: User Similarity in a Social Network without Edge Weight
Input
SQL-MapReduce Call
Output
Example 2: User Similarity in a Social Network with Edge Weight
Input
SQL-MapReduce Call
Output
Example 3: User Similarity and Product Recommendation
Input
SQL-MapReduce Call
Output
Example 4: Using the Sources and Targets Tables as Inputs
Input
SQL-MapReduce Call
Output
RandomWalkSample
Summary
Background
Usage
RandomWalkSample Syntax
Arguments
Input
Output
Example
Input
SQL-GR Call
Output
Neural Networks
Neural Networks
Introduction to Neural Networks
NeuralNet
Summary
Usage
NeuralNet Syntax
Arguments
Input
Weights Table
Output
Example
Input
Split Input into Training and Testing Data Sets
SQL-MapReduce Call
Output
NeuralNetPredict
Summary
Usage
NeuralNetPredict Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Calculating Prediction Accuracy
Data Transformation
Data Transformation
Antiselect
Summary
Usage
Antiselect Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Apache_Log_Parser
Summary
Background
Apache Log Configuration
Apache Log Parser Item-Name Mapping
Usage
Apache_Log_Parser Syntax
Arguments
Input
Output
Examples
Input
Example 1: Default Extended/Combined Log Format
SQL-MapReduce Call
Output
Example 2: Common logformat
SQL-MapReduce Call
Output
Categorize
Summary
Usage
Categorize Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
Fellegi-Sunter Functions
Summary
Background
FellegiSunterTrainer
Summary
Usage
FellegiSunterTrainer Syntax
Arguments
Input
Output
Examples
Input
SQL to generate FellegiSunterTrainer input from output of StringSimilarity function
Example 1: Unsupervised Learning
SQL-MapReduce Call
Output
Example 2: Supervised Learning
SQL-MapReduce Call
Output
FellegiSunterPredict
Summary
Usage
FellegiSunterPredict Syntax
Arguments
Input
Output
Examples
Input
SQL to generate FellegiSunterTrainer input from StringSimilarity function
Example 1: Use Unsupervised Learning Model (fg_unsupervised_model)
SQL-MapReduce Call
Output
Example 2: Use supervised learning model (fg_supervised_model)
SQL-MapReduce Call
Output
Geometry Functions
GeometryLoader
Summary
Usage
GeometryLoader Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
SQL-MapReduce Call
Output
PointInPolygon
Summary
Background
Usage
PointInPolygon Syntax
Small Polygon Count and Large Point Count
Large Polygon Count and Small Point Count
Only to Determine Relations of Points and Polygons in Same Group
Arguments
Input
Output
Examples
Example 1: With OutputAll ('true')
Input
SQL-MapReduce Call
Output
Example 2: With OutputAll ('false')
SQL-MapReduce Call
Output
Example 3: Passenger Coordinates as Separate Columns
Input
SQL-MapReduce Call
Output
GeometryOverlay
Summary
Usage
GeometryOverlay Syntax
UNION, INTERSECTION, DIFFERENCE and SYMDIFFERENCE
CONVEXHULL
BUFFER
Arguments
Input
Output
Examples
Input
Example 1: Intersection
SQL-MapReduce Call
Output
Example 2: Union
SQL-MapReduce Call
Output
Example 3: Buffer (Single Input)
SQL-MapReduce Call
Output
IdentityMatch
Summary
Background
Usage
IdentityMatch Syntax
When Reference Data Fits in Memory
When Reference Data Does Not Fit in Memory
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
IPGeo
Summary
Usage
IPGeo Syntax
Arguments
Input
Output
Examples
Input
Example 1: Specify Location of IP Database
SQL-MapReduce Call
Example 2: IP Database Stored as Aster Database File
SQL-MapReduce Call
Example 3: Use Default Maxmind Geolite Database
SQL-MapReduce Call
Output
Extending IPGeo
JSONParser
Summary
Background
Usage
JSONParser Syntax
Arguments
Input
Output
Examples
Example 1: With Nondefault Options
Input
SQL-MapReduce Call
Output
Example 2: With Default Argument Values
Input
SQL-MapReduce Call
Output
Example 3: Parsing with Ancestor (Search Path Argument Specified)
Input
SQL-MapReduce Call
Output
Example 4: Specifying ERROR_HANDLER When Calling JSONParser
Input
SQL-MapReduce Call
Output
Multi_Case
Summary
Usage
Multi_Case Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
MurmurHash
Summary
Background
Usage
MurmurHash Syntax
Arguments
Input
Output
Examples
Input
Example 1: 32-Bit Hash Value (by Default)
SQL-MapReduce Call
Output
Example 2: 64-Bit Value (Specified)
SQL-MapReduce Call
Output
OutlierFilter
Summary
Usage
OutlierFilter Syntax
Arguments
Input
Output
Examples
Input
Example 1: Method ('percentile'), ReplacementValue ('null')
SQL-MapReduce Call
Output
Example 2: Method ('MAD-median'), ReplacementValue ('median')
SQL-MapReduce Call
Output
Pack
Summary
Usage
Pack Syntax
Arguments
Input
Output
Examples
Input
Example 1: Default Options
SQL-MapReduce Call
Output
Example 2: Nondefault Options
SQL-MapReduce Call
Output
Pivot
Summary
Usage
Pivot Syntax
Arguments
Input
Ordering Input Data
Output
Examples
Input
Example 1: Specify Maximum Number of Rows in Any Partition
SQL-MapReduce Call
Output
Example 2: Specify Pivot Keys
SQL-MapReduce Call
Output
Example 1: Use Default Pivot Keys
SQL-MapReduce Call
Output
PSTParserAFS
Summary
Usage
Verifying that AFS is Working
PSTParserAFS Syntax
Arguments
Input
Output
Alternative Way to Run PSTParserAFS
Examples
Example 1: Single PST File, Default Output Fields
Input
SQL-MapReduce Call
Output
Example 2: Single PST File, Specified Output Fields
Input
SQL-MapReduce Call
Output
Example 3: Directory of PST Files, Exclude Argument
Example 4: Path and Exclude Arguments with Regular Expressions
Example 5: Multiple PST Files, Specified Host and AFS Server Port Attributes
Example 6: Using table_from_afs
Scale Functions
Summary
Background
ScaleMap
Usage
ScaleMap Syntax
Arguments
Input
Invalid Input Data Handling
Output
Scale
Usage
Scale Syntax
Arguments
Input
Output
ScalePrinter
Usage
ScalePrinter Syntax
Input
Output
PartitionScale
Usage
PartitionScale Syntax
Arguments
Input
Output
Scale Function Examples
Example 1: Scale with Method('midrange')
Input
SQL-MapReduce Call
Output
Example 2: Scale with Method('midrange') and Intercept(-min)
Input
SQL-MapReduce Call
Output
Example 3: Use Training Data to Scale Test Data
Input
Step 1: Create Statistics Table from Training Data
Step 2: Scale Test Data
Output
Example 4: ScalePrinter
SQL-MapReduce Call
Output
Example 5: Scale with Multiple Methods
Input
SQL-MapReduce Call
Output
Example 6: PartitionScale
Input
SQL-MapReduce Call
Output
Example 7: Using Scale Output in KMeans
Input
Step 1: Use Scale to Create Table of Scaled Data
Step 2: Input Scaled Data to KMeans
Output
StringSimilarity
Summary
Usage
StringSimilarity Syntax
Arguments
Input
Output
Examples
Input
Example 1: Comparison of src_text1 with tar_text
SQL-MapReduce Call
Output
Example 2: Comparison of src_text2 with tar_text
SQL-MapReduce Call
Output
Unpack
Summary
Usage
Unpack Syntax
Arguments
Input
Output
Examples
Example 1: Delimiter Separates Virtual Columns
Input
SQL-MapReduce Call
Output
Example 2: No Delimiter Separates Virtual Columns
Input
SQL-MapReduce Call
Output
Unpivot
Summary
Usage
Unpivot Syntax
Arguments
Input
Output
Examples
Input
Example 1: Specified Unpivot Columns, Default Optional Values
SQL-MapReduce Call
Output
Example 2: Specified Unpivot Columns, Specified Optional Values
SQL-MapReduce Call
Output
Example 3: Specified Unpivot Range, Default Optional Values
SQL-MapReduce Call
Output
URIPack
Summary
Usage
URIPack Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
URIUnpack
Summary
Background
Usage
URIUnpack Syntax
Arguments
Input
Output
Example
Input
SQL-MapReduce Call
Output
XMLParser
Summary
Background
Usage
XMLParser Syntax
Arguments
Input
Output
Examples
Example 1: Specify Sibling and Sibling_Delimiter
Input
SQL-MapReduce Call
Output
Example 2: Specify Ancestor
Input
SQL-MapReduce Call
Output
Example 3: Use Regular Expressions in Nodes and Ancestor
Input
SQL-MapReduce Call
Output
Example 4: Handle Errors
Input
SQL-MapReduce Call
Output
Example 5: Show Grandparent, Parent, and Child Nodes
Input
SQL-MapReduce Call
Output
XMLRelation
Summary
Usage
XMLRelation Syntax
Arguments
Input
Output
Output ('fulldata')
Output ('parentchild')
Output ('fullpath')
Examples
Example 1: Output Three Different Output Table Schemas
Input
SQL-MapReduce Call 1
Output
SQL-MapReduce Call 2
Output
SQL-MapReduce Call 3
Output
Example 2: Output Attributes as Nodes
Input
SQL-MapReduce Call
Output
Example 3: Enable Error Handling
Input
SQL-MapReduce Call
Output
Aster Scoring SDK
Aster Scoring SDK
Introduction to Aster Scoring SDK
AMLGenerator
Summary
Usage
AMLGenerator Syntax
Arguments
Input
Output
Header
Request Columns
Request Parameters
Model Columns
Model Data
Example
Input
SQL-MapReduce Call
Output
Scorer
Summary
Multiple Scorer Configuration
Cloud Integration
Package
Installation
Using classpath
Eclipse
Functional Support
Scorer Input Formats
CSVInputFormat
AMLInputFormat
Data Types
Scorer Output Formats
API
Logging
Scoring API
Scoring Requests from File System
Scoring Requests Using API
Javadoc
Examples
Logging Support
Compatibility
Performance
Tips
Aster Scoring SDK Functions
Aster Scoring SDK Single Decision Tree
Model Format
Request Definition
Parameters
Aster Scoring SDK Generalized Linear Model
Model Format
Request Definition
Parameters
Aster Scoring SDK Random Forest
Model Format
Request Definition
Parameters
Aster Scoring SDK Naïve Bayes
Model Format
Request Definition
Parameters
Aster Scoring SDK Naïve Bayes Text Classifier
Model Format
Request Definition
Parameters
Aster Scoring SDK Text Tagging
Model Format
Request Definition
Parameters
Additional Notes
Example 1
Example 2
Example 3
Example 4
Aster Scoring SDK Extract Sentiment
Model Format
Request Definition
Parameters
Additional Notes
Example 1
Example 2
Example 3
Example 4
Aster Scoring SDK Text Parser
Model Format
Request Definition
Parameters
Additional Notes
Example 1
Example 2
Example 3
Aster Scoring SDK Text Tokenizer
Model Format
Request Definition
Parameters
Additional Notes
Example 1
Example 2
Example 3
Aster Scoring SDK SparseSVM
Model Format
Request Definition
Parameters
Aster Scoring SDK CoxPH
Model Format
Request Definition
Parameters
Aster Scoring SDK LDAInference
Model Format
Request Definition
Parameters
FAQ
How is Aster Scoring SDK different from functions in the Aster Analytics suite?
Does Aster Scoring SDK include a real-time streaming engine or a listening framework?
Does Aster Scoring SDK Need Aster Database and Aster Analytics Suite?
Can Aster Scoring SDK be invoked in a cloud environment such as Amazon Web Services (AWS)?
Is Aster Scoring SDK thread-safe? Can it be deployed in a multithreaded parallel system?
What is the recommended way to incorporate Aster Scoring SDK in a multithreaded system?
Does Aster Scoring SDK work on Predictive Model Markup Language (PMML) based models?
How fast is the response time of Aster Scoring SDK?
Visualization Functions
Visualization Functions
Aster Database System Utility Functions
Aster Database System Utility Functions
List of Functions and Their Syntax
Organization of List of Functions
Time Series, Path, and Attribution Analysis
Arima (version 1.1)
ArimaPredictor (version 1.1)
Attribution (Multiple-Input Version) (version 2.3)
Attribution (Single-Input Version) (version 2.3)
Burst (version 1.0)
CCM (version 1.0)
CCMPrepare (version 1.0)
ChangePointDetection (version 1.0)
DTW (version 1.0)
DWT (version 1.3)
DWT2D (version 1.3)
FrequentPaths (version 2.1)
IDWT (version 1.3)
IDWT2D (version 1.3)
Interpolator (version 1.0)
Path_Analyzer (version 1.3)
Path_Generator (version 1.3)
Path_Start (version 1.2)
Path_Summarizer (version 1.2)
RtChangePointDetection (version 1.0)
SAX2
Multiple-Input Version
Single-Input Version
SeriesSplitter (version 1.0)
Sessionize (version 1.3)
SupervisedShapeletClassifier (version 1.1)
SupervisedShapeletTrainer (version 1.1)
UnsupervisedShapelet (version 1.0)
VARMAX (version 1.0)
Pattern Matching with Teradata Aster nPath
nPath (version 1.0)
Statistical Analysis
AddOnePlayer (version 1.0)
Approximate Distinct Count (version 1.0)
Approximate Percentile (version 1.1)
CMAVG (version 1.2)
ConfusionMatrix (version 2.0)
Correlation (version 1.4)
CoxPH (version 1.2)
CoxPredict (version 1.1)
CoxSurvFit (version 1.1)
CrossValidation (version 1.0)
Distribution Matching, Hypothesis-Test Mode
Continuous Distributions
Option 1: For Multiple-Node Data Sets
Option 2: For Single-Node Data Sets
Discrete Distributions
Option 1: For Multiple-Node Data Sets
Option 2: For Single-Node Data Sets and Any CvM Test
Distribution Matching, Best-Match Mode
DOUBLE PRECISION Input
Integer Input
EMAVG (version 1.2)
FMeasure (version 1.4)
GenerateCombination (version 1.0)
GLM (version 1.7)
GLMPredict (version 1.5)
Histogram (version 1.0)
HMMDecoder (version 1.3)
HMMEvaluator (version 1.3)
HMMSupervisedLearner (version 1.3)
HMMUnsupervisedLearner (version 1.3)
KNN (version 1.3)
LARS (version 1.1)
LARSPredict (version 1.1)
Linear Regression (version 1.1 and 1.0, respectively)
LRTEST (version 1.1)
Percentile (version 1.0)
Principal Component Analysis (PCA_Reduce version 1.2, PCA_Map, version 1.1)
PCAPlot (version 1.0)
RandomSample (version 1.0)
Sample (version 1.2)
Unconditional Sampling, Single Sample Rate
Unconditional Sampling, Approximate Sample Size
Conditional Simple Sampling, Single Sample Rate
Conditional Sampling, Variable Sample Rates
Conditional Sampling, Approximate Sample Size
Conditional Sampling, Variable Approximate Sample Sizes
SMAVG (version 1.2)
SortCombination (version 1.1)
Support Vector Machine (SVM) Functions
DenseSVMModelPrinter (version 1.1)
DenseSVMPredictor (version 1.1)
DenseSVMTrainer (version 1.1)
SparseSVMPredictor (version 1.1)
SparseSVMTrainer (version 1.1)
SVMModelPrinter (version 1.1)
VectorDistance (version 1.1)
VWAP (version 1.2)
WMAVG (version 1.2)
Text Analysis
Evaluate Named Entity Finder (version 1.1)
EvaluateSentimentExtractor (version 1.1)
ExtractSentiment (version 3.1)
FindNamedEntity (version 1.2)
LDAInference (version 1.1)
LDATopicPrinter (version 1.1)
LDATrainer (version 1.1)
Levenshtein Distance (LDist) (version 1.1)
NaiveBayesTextClassifierPredict (version 1.1)
NaiveBayesTextClassifierTrainer (version 1.1)
NER (version 1.1)
NEREvaluator (version 1.1)
NERTrainer (version 1.1)
nGram (version 1.5)
POSTagger (version 2.1)
Sentenizer (version 1.1)
TextChunker (version 1.2)
TextClassifier (version 1.2)
TextClassifierEvaluator (version 1.2)
TextClassifierTrainer (version 1.4)
TextMorph (version 1.2)
TextTagging (version 1.3)
TextTokenizer (version 3.2)
Text_Parser (version 1.3)
TF_IDF (TF_IDF version 2.1, TF version 1.1)
TrainNamedEntityFinder (version 1.3)
TrainSentimentExtractor (version 2.1)
Cluster Analysis
Canopy (version 2.0)
GMMFit (version 1.0)
GMMPredict (version 1.0)
GMMProfile (version 1.0)
KMeans (version 1.6)
KMeansPlot Syntax
KModes (version 1.0)
KModesPredict (version 1.0)
Minhash (version 2.2)
Naive Bayes
NaiveBayesMap and NaiveBayesReduce (version 1.3)
NaiveBayesPredict (version 1.4)
Ensemble Methods
AdaBoost_Drive (version 1.5)
AdaBoost_Predict (version 1.5)
Forest_Analyze (version 1.1)
Forest_Drive (version 1.5)
Forest_Predict (version 1.5)
Single_Tree_Drive (version 1.3)
Single_Tree_Predict (version 1.2)
Association Analysis
Basket_Generator (version 1.3)
CFilter (version 1.7)
FPGrowth (version 1.2)
KNNRecommenderPredict (version 1.0)
KNNRecommenderTrain (version 1.0)
WSRecommender (version 1.0)
Graph Analysis
AllPairsShortestPath (version 1.2)
Betweenness (version 1.2)
Closeness (version 1.2)
EigenvectorCentrality (version 1.1)
gTree (version 1.0)
LocalClusteringCoefficient (version 1.1)
LoopyBeliefPropagation (version 1.0)
Modularity (version 1.1)
nTree (version 1.1)
PageRank (version 1.1)
pSALSA (version 1.1)
RandomWalkSample (version 1.2)
Neural Networks
NeuralNet (version 1.0)
NeuralNetPredict (version 1.0)
Data Transformation
Antiselect (version 1.0)
Apache_Log_Parser (version 2.2)
Categorize (version 1.0)
FellegiSunterPredict (version 1.1)
FellegiSunterTrainer (version 1.1)
GeometryLoader (version 1.1)
GeometryOverlay (version 1.1)
UNION, INTERSECTION, DIFFERENCE and SYMDIFFERENCE
CONVEXHULL
BUFFER
IdentityMatch (version 1.1)
When Reference Data Fits in Memory
When Reference Data Does Not Fit in Memory
IPGeo (version 2.1)
JSONParser (version 1.5)
Multi_Case (version 1.1)
MurmurHash (version 1.1)
OutlierFilter (version 1.3)
Pack (version 1.2)
PartitionScale (version 1.2)
Pivot (version 1.5)
PointInPolygon
Small Polygon Count and Large Point Count
Large Polygon Count and Small Point Count
Only to Determine Relations of Points and Polygons in Same Group
PSTParserAFS (version 1.1)
Scale (version 1.2)
ScaleMap (version 1.2)
ScalePrinter (version 1.2)
StringSimilarity (version 1.1)
Unpack (version 1.2)
Unpivot (version 1.2)
URIPack (version 1.1)
URIUnpack (version 1.0)
XMLParser (version 1.7)
XMLRelation (version 1.3)
Aster Scoring SDK
AMLGenerator (version 1.0)
Scorer
Aster Scoring SDK Single Decision Tree
Aster Scoring SDK Generalized Linear Model
Aster Scoring SDK Random Forest
Aster Scoring SDK Naïve Bayes
Aster Scoring SDK Naïve Bayes Text Classifier
Aster Scoring SDK Text Tagging
Aster Scoring SDK Extract Sentiment
Aster Scoring SDK Text Parser
Aster Scoring SDK Text Tokenizer
Aster Scoring SDK SparseSVM
Aster Scoring SDK CoxPH
Aster Scoring SDK LDAInference
Visualization Functions
Problem: The function runs slowly for large graphs or terminates unsuccessfully, displaying a failure message on the console.
Work Arounds:
Consult the logs for error message details and troubleshooting.
The logs can help determine the time taken for each iteration. If you know the number of iterations that the function takes (usually 25-50), you can estimate the total execution time.
All graph functions operate much faster on INTEGER and BIGINT single-column vertex ids. To generate an INTEGER vertex based graph, see Tips section above.
Compute the modularity in incremental steps by choosing a subset of nodes using the Sources argument.
If you already know some of the groupings in the graph, specify them with the CommunityAssociation argument.
If you specified the CommunityEdgeTable argument, the reason for the slow execution might be that the function is writing the community table to the database through JDBC. Run the function without the CommunityEdgeTable argument first, to obtain the modularity of the resultant graph.
Problem: The function terminates with errors on the vertices table or edges table.
Work Arounds:
Consult the logs for error message details and troubleshooting.
Ensure that all source and target vertices in the edges table are listed in the vertices table. Ensure that the columns representing source and target vertices are not NULL.
Problem: The function completes successfully; however, the results do not show a good modularity score or community detection.
Work Arounds:
Change the value of seed.
Multiply the edge weights by a constant.
Change the values in the Resolution argument.
If you already know some of the groupings in the graph, specify them with the CommunityAssociation argument.
Problem: The modularity score is poor.
Explanation: It may be that the graph has no inherent community structure.