Vector 6.2 and Vector 6.3 Delta/New Features

Vector 6.2 and Vector 6.3 Delta/New Features

Many new features and functionality upgrades have been provided with the releases of Vector 6.2 and 6.3. In this course we bring together the learning content for each new or upgraded piece of functionality together with a short quiz to help reinforce the information provided.

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About this course

At the end of this course you will:

Have gained an understanding for how to implement the new features introduced in the Vector 6.2 and Vector 6.3 releases.  
Course Style:
The content is presented in a how to style in order for you to follow along within your own database environment
Audience:
For System or Database Administrators who have responsibility for maintaining and optimizing the Corporate Databases and Data Warehouses.
Prerequisites:

Functionality available from Vector 6.2 and Vector 6.3.
Resource Links:
Software Download: https://esd.actian.com/
Actian Community:  https://communities.actian.com
Documentation:  https://docs.actian.com/

 

Curriculum168 min

  • Course Objective 1 min
  • Vector 6.2 New Features
  • Automatic Table Partitioning 5 min
  • Query Result Caching and Spill to Disk 8 min
  • LISTAGG Aggregation Functionality 3 min
  • Using NumPy (Numerical Python) and the handling of NULLS within a Vector User Defined Function (UDF) 10 min
  • Encryption Key Management via SQL Commands 2 min
  • Vector 6.2: Workload Management
  • Overview 6 min
  • Create Queues and Configurations 7 min
  • Enable, Disable, Audit and Monitor 6 min
  • Vector 6.2: Spark Vector Connector 3.0
  • Introduction to Apache Spark 3.0 and Installation of Spark 3.0 for Vector 6 min
  • Configuring the Vector Spark Provider - Primer 5 min
  • Configuring the Vector Spark Provider 7 min
  • Importing Data from Amazon S3 Bucket into a Vector Instance 4 min
  • Exporting Data from a Vector Database into External Files 3 min
  • Data Migration using Spark Connector 4 min
  • New Spark Connector 3.0 Feature: Staging Table 6 min
  • New Spark Connector 3.0 Feature: Using a Staging Table to Unnest Source Schema 6 min
  • Vector 6.2: Bulk and Batch Data Loading Operations Explained
  • Introduction 3 min
  • Bulk and Batch Operations 5 min
  • Modify To Combine 8 min
  • Vector 6.2: User Defined Functions: Containerized and non-containerized deployment, process control/cancellation, log message output and importing libraries/modules
  • Containerized/Non-Containerized UDFs and UDF process control/cancellation 9 min
  • UDF log message output and importing libraries/modules into UDFs 7 min
  • Vector 6.3 New Features
  • Automatic Log Rotation 6 min
  • UDF Engine Startup 3 min
  • Database Procedure Exception Handling 6 min
  • Pattern Matching - SIMILAR_TO 5 min
  • Extending UDF Accessibility 3 min
  • Remote File Support 6 min
  • Smart MinMax Index 7 min
  • Incremental Rollforwarddb Hot Backup (Warm Standby) 5 min
  • Data Loading and Data Export Updates 4 min
  • Course Certification Quiz
  • Vector 6.2 and 6.3 Course Quiz
  • Feedback
  • Take Course Survey 1 min

About this course

At the end of this course you will:

Have gained an understanding for how to implement the new features introduced in the Vector 6.2 and Vector 6.3 releases.  
Course Style:
The content is presented in a how to style in order for you to follow along within your own database environment
Audience:
For System or Database Administrators who have responsibility for maintaining and optimizing the Corporate Databases and Data Warehouses.
Prerequisites:

Functionality available from Vector 6.2 and Vector 6.3.
Resource Links:
Software Download: https://esd.actian.com/
Actian Community:  https://communities.actian.com
Documentation:  https://docs.actian.com/

 

Curriculum168 min

  • Course Objective 1 min
  • Vector 6.2 New Features
  • Automatic Table Partitioning 5 min
  • Query Result Caching and Spill to Disk 8 min
  • LISTAGG Aggregation Functionality 3 min
  • Using NumPy (Numerical Python) and the handling of NULLS within a Vector User Defined Function (UDF) 10 min
  • Encryption Key Management via SQL Commands 2 min
  • Vector 6.2: Workload Management
  • Overview 6 min
  • Create Queues and Configurations 7 min
  • Enable, Disable, Audit and Monitor 6 min
  • Vector 6.2: Spark Vector Connector 3.0
  • Introduction to Apache Spark 3.0 and Installation of Spark 3.0 for Vector 6 min
  • Configuring the Vector Spark Provider - Primer 5 min
  • Configuring the Vector Spark Provider 7 min
  • Importing Data from Amazon S3 Bucket into a Vector Instance 4 min
  • Exporting Data from a Vector Database into External Files 3 min
  • Data Migration using Spark Connector 4 min
  • New Spark Connector 3.0 Feature: Staging Table 6 min
  • New Spark Connector 3.0 Feature: Using a Staging Table to Unnest Source Schema 6 min
  • Vector 6.2: Bulk and Batch Data Loading Operations Explained
  • Introduction 3 min
  • Bulk and Batch Operations 5 min
  • Modify To Combine 8 min
  • Vector 6.2: User Defined Functions: Containerized and non-containerized deployment, process control/cancellation, log message output and importing libraries/modules
  • Containerized/Non-Containerized UDFs and UDF process control/cancellation 9 min
  • UDF log message output and importing libraries/modules into UDFs 7 min
  • Vector 6.3 New Features
  • Automatic Log Rotation 6 min
  • UDF Engine Startup 3 min
  • Database Procedure Exception Handling 6 min
  • Pattern Matching - SIMILAR_TO 5 min
  • Extending UDF Accessibility 3 min
  • Remote File Support 6 min
  • Smart MinMax Index 7 min
  • Incremental Rollforwarddb Hot Backup (Warm Standby) 5 min
  • Data Loading and Data Export Updates 4 min
  • Course Certification Quiz
  • Vector 6.2 and 6.3 Course Quiz
  • Feedback
  • Take Course Survey 1 min