Advanced SQL Engine (was NewSQL Engine) analytic functions are specifically for analyzing data. Data can include clickstreams, financial transaction data, and user interaction data.
| Function Name | Description |
|---|---|
| Antiselect (SQL Engine) | AntiSelect returns all columns except those specified. |
| Attribution (SQL Engine) | Calculates attributions with a wide range of distribution models. Often used in web-page analysis. |
| DecisionForestPredict (SQL Engine) | Uses the model file output by Machine Learning Engine (ML Engine) DecisionForest function to analyze the input data and make predictions. |
| DecisionTreePredict (SQL Engine) | Uses the model file output by ML Engine DecisionTree function to analyze the input data and make predictions. |
| GLMPredict (SQL Engine) | Uses the model file output by ML Engine GLM function to analyze the input data and make predictions. |
| MovingAverage (SQL Engine) | Computes average values in a series. |
| NaiveBayesPredict (SQL Engine) | Uses the model file output by ML Engine Naive Bayes Classifier function to analyze the input data and make predictions. |
| NaiveBayesTextClassifierPredict (SQL Engine) | Uses the model file output by ML Engine NaiveBayesTextClassifierTrainer function to analyze the input data and make predictions. |
| NGramSplitter (SQL Engine) | Tokenizes (splits) an input stream and emits n multigrams, based on specified delimiter and reset parameters. Useful for sentiment analysis, topic identification, and document classification. |
| nPath® (SQL Engine) | Performs regular pattern matching over a sequence of rows from one or more inputs. |
| Pack (SQL Engine) | Compresses data in multiple columns into a single packed data column. |
| Sessionize (SQL Engine) | Maps each click in a clickstream to a unique session identifier. |
| StringSimilarity (SQL Engine) | Calculates the similarity between two strings, using the specified comparison method. |
| SVMSparsePredict (SQL Engine) | Uses the model file output by ML Engine SVMSparse function to analyze the input data and make predictions. |
| Unpack (SQL Engine) | Expands data from a single packed column to multiple unpacked columns. |
Advanced SQL Engine analytic functions have corresponding ML Engine functions. The syntax of corresponding functions may differ, but given the same inputs and syntax element values, they produce the same results (with the minor exceptions noted in specific functions).
To execute ML Engine functions on Teradata Vantage™, contact your Teradata Support representative.
Data Cleaning Functions
| Function Name | Description |
|---|---|
| TD_ConvertTo | Converts the specified input table columns to specified data types. |
| TD_GetRowsWithoutMissingValues | Displays the rows that have non-NULL values in the specified input table columns. |
| TD_OutlierFilterFit | Calculates the lower_percentile, upper_percentile, count of rows, and median for the specified input table columns. |
| TD_OutlierFilterTransform | Filters outliers from the input table |
| TD_SimpleImputeFit | Outputs a table of values to substitute for missing values in the input table. |
| TD_SimpleImputeTransform | Substitutes specified values for missing values in the input table. |
Data Exploration Functions
| Function Name | Description |
|---|---|
| TD_CategoricalSummary | Displays the distinct values and their counts for each specified input table column. |
| TD_ColumnSummary | Displays a summary of each specified input table column. |
| TD_GetRowsWithMissingValues | Displays the rows that have NULL values in the specified input table columns. |
| TD_Histogram | Calculates the frequency distribution of a data set. |
| TD_QQNorm | Checks whether the values in the specified input table columns are normally distributed. |
| TD_UnivariateStatistics | Displays descriptive statistics for each specified numeric input table column. |
| TD_WhichMax | Displays all rows that have the maximum value in a specified input table column. |
| TD_WhichMin | Displays all rows that have the minimum value in specified input table column. |
Feature Engineering Transform Functions
| Function Name | Description |
|---|---|
| TD_BinCodeFit | Converts numeric data to categorical data by binning the numeric data into multiple numeric bins (intervals). |
| TD_BinCodeTransform | Transforms input table columns from the BinCodeFit function output. |
| TD_FunctionFit | Determines whether specified numeric transformations can be applied to specified input columns. |
| TD_FunctionTransform | Applies numeric transformations to input columns to the FunctionFit output. |
| TD_OneHotEncodingFit | Outputs a table of attributes and categorical values to the TD_OneHotEncodingTransform function. |
| TD_OneHotEncodingTransform | Encodes specified attributes and categorical values as one-hot numeric vectors using the output from the TD_OneHotEncodingFit function. |
| TD_PolynomialFeaturesFit | Stores all the specified values in the argument in a tabular format. |
| TD_PolynomialFeaturesTransform | Extracts values of arguments from the output of the TD_PolynomialFeaturesFit function and generates a feature matrix of all polynomial combinations of the features. |
| TD_RowNormalizeFit | Outputs a table of parameters and specified input columns to TD_RowNormalizeTransform which normalizes the input columns row-wise. |
| TD_RowNormalizeTransform | Normalizes the input columns row-wise using the output of the TD_RowNormalizeFit function. |
| TD_ScaleFit | Outputs a table of statistics to the TD_ScaleTransform function. |
| TD_ScaleTransform | Scales the specified input table columns using the output of the TD_ScaleFit function. |
Feature Engineering Utility Functions
| Function Name | Description |
|---|---|
| TD_FillRowID | Adds a column of unique row identifiers to the input table. |
| TD_NumApply | Applies a specified numeric operator to the specified input table columns. |
| TD_RoundColumns | Rounds the values of each specified input table column to a specified number of decimal places |
| TD_StrApply | Applies a specified string operator to the specified input table columns. |
Hypothesis Testing Functions
| Function Name | Description |
|---|---|
| TD_ChiSq | Performs Pearson's chi-squared test for independence. |
| TD_FTest | Performs an F-test, for which the test statistic has an F-distribution under the null hypothesis. |
| TD_ZTest | Performs a Z-test, for which the distribution of the test statistic under the null hypothesis can be approximated by normal distribution. |
More Information
| Topic | Reference |
|---|---|
| ML Engine functions | Teradata Vantage™ Machine Learning Engine Analytic Function Reference, B700-4003 |
| Aster Analytics functions | Teradata Aster® Analytics Foundation User Guide, B700-1022 |
| Installing model files output by ML Engine functions on Advanced SQL Engine | Teradata Vantage™ User Guide, B700-4002 |