These enhancements were added.
Create, Use, and Migrate User-defined Functions to VantageCloud Lake
You can create and manage SQL and C or C++ user-defined functions (UDFs) in VantageCloud Lake. Scalar UDFs, aggregate UDFs, and table operators can run on the primary cluster or on compute clusters. Table functions currently run only on the primary cluster.
You can also migrate SQL scripts (BTEQ files) that create C or C++ UDFs in VantageCloud Enterprise or VantageCore to VantageCloud Lake.
See Creating, Using, and Migrating UDFs to VantageCloud Lake.
Bring Your Own Model
Data Scientists and Data Analysts can now insert existing predictive Dataiku models to a Vantage model table and score data in Vantage. See Bring Your Own Model.
QueryGrid
- VantageCloud Enterprise on AWS
- VantageCore (on-premises)
- VantageCloud Lake for Teradata-to-Teradata connectivity
See Ecosystem Applications and Compatibility Matrix for VantageCloud Lake Ecosystem Applications.
Consumption
The Consumption page provides visibility into an organization's compute and storage utilization. The page has the monthly consumption breakdown for the environment and organizations. You can refine the interval. For example, you can view hourly intervals to ensure that compute clusters are available during high-demand periods and inactive during low-demand periods. Weekly and monthly intervals help you assess overall usage and manage costs based on use.
Bring Your Own Identity Provider
An identity provider stores, secures, and authenticates the digital identities of users. You can use your corporate identity provider (IDP) with VantageCloud Lake to authenticate users.
New Analytic Functions
- TD_GLMPerSegment: Trains a whole data set by partitioning, and creates a single model for each partition.
- TD_GLMPredictPerSegment: Predicts target value (regression) and class label (classification) for test data using a corresponding GLM model trained using TD_GLMPerSegment.
- TD_TargetEncodingFit: Generates hyperparameters for use by TD_TargetEncodingTransform. See TD_TargetEncodingFit.
- TD_TargetEncodingTransform: Uses the hyperparameters generated by TD_TargetEncodingFit to encode categorical values. See TD_TargetEncodingTransform.
TD_GLMPredict Syntax Update
Information about syntax change for TD_GLMPredict is added. The Model alias is updated to ModelTable in the ON clause syntax for TD_GLMPredict. See TD_GLMPredict Syntax.
ALTER TABLE SAVE | UNSAVE Update
The ALTER TABLE SAVE | UNSAVE command now lets you save and unsave based on version number. See ALTER TABLE SAVE | UNSAVE Syntax.
SELECT ... AS OF version_number
You can now select data from a table based on version number. See SELECT … AS OF version_number.
InDB Analytic Functions Explorer
The InDB Analytic Functions Explorer lets you discover, explore, and experiment with InDB analytic functions without writing code. You can access it from the Editor of the VantageCloud Lake Console. In this first version, it supports the SQLMR analytic functions. See In-DB Analytic Functions Explorer.
nPath Visualization
nPath Visualization helps you find hidden data patterns and analyze time series events data. nPath is especially useful when your goal is to identify the paths that lead to an outcome. For example, you can use nPath to analyze events including successful sales, fraudulent activities, and patient journeys. See nPath Visualization.
APPLY Table Operator
DATE with format YYYY-MM-DD is now a supported data type for the APPLY table operator. See APPLY Table Operator Data Types.