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Advanced ECL (Part 1) – Working with Relational Data - Atlanta

HPCC Systems

Monday, July 16, 2018 at 1:00 PM - Wednesday, July 18, 2018 at 12:00 PM (EDT)

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Ticket Type Sales End Price Fee Quantity
Attendee Jul 13, 2018 $1,995.00 $0.00

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Event Details

 

NOTE: RELX and LexisNexis employees should register using the approved promo code provided by their manager or contact training@hpccsystems.com.

Advanced ECL (Part 1) – Working with Relational Data

This class examines in detail the ECL functions that make it easy to work with Relational data in the HPCC Systems platform. ECL began as an extremely powerful query language built around easily querying into Relational Data. The techniques taught here reveal that power to its fullest.

Note: This course is the first in a two-part advanced series. People who attend the Advanced ECL (Part 1) – Working with Relational Data class, should also attend the Advanced ECL (Part 2) – Super files, Working with XML, and Free-form Text Parsing. Both classes are presented in the same week.

Course Length: 2 days

Class Prerequisites: Students must have attended the  Introduction to ECL (Part 1) - Concepts and Queries and Introduction to ECL (Part 2) – Super files, Working with XML, and Free-form Text training classes. Students are welcome to bring their own laptops to take away the code and examples from the class.

Topics include:

  • Creating hierarchical relational datasets (Nested Child Datasets)
  • Nested Child Dataset Definitions (RECORD/DATASET)
  • NORMALIZE and DENORMALIZE
  • Complex Multi-level Relational Querying

Class begins Monday at 1pm and concludes at 5pm.
Class begins Tuesday at 9am and concludes at 5pm.
Class begins Wednesday at 9am and concludes at 12pm.

Have questions about Advanced ECL (Part 1) – Working with Relational Data - Atlanta? Contact HPCC Systems

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When & Where


LexisNexis
1000 Alderman Drive
Training Center
Alpharetta, GA 30005

Monday, July 16, 2018 at 1:00 PM - Wednesday, July 18, 2018 at 12:00 PM (EDT)


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Organizer

HPCC Systems

HPCC Systems is an open source, massive parallel-processing computing platform for big data processing and analytics.

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