BlinkDB and G-OLA: Supporting Continuous Answers with Error Bars in SparkSQL

Big datasets are growing exponentially, but our needs to get quick interactive responses to our queries remain ever as important. This talk will feature an overview of various components in BlinkDB and introduce a new generalized online aggregation (G-OLA) paradigm in SparkSQL to incrementally process massive amounts of data on clusters of tens, hundreds or thousands of machines while returning approximate answers. More precisely, this new execution model enables SparkSQL to present the user with meaningful approximate results (with error bars) that are continuously refined and updated, at a speed comfortable to the user, while it crunches larger and larger fractions of the whole dataset in the background. This not only alleviates the need for pre-processing the data in advance for a wide range of queries, but also enables the users to observe the progress of a query and control its execution on the fly– enabling a smooth time/accuracy trade-off.

Knoldus is organizing an one hour session on 24th Nov 2015 at 6:00 PM. Mr. Sameer Agarwal (https://spark-summit.org/2015/speakers/sameer-agarwal/) from Databricks would give session on "BlinkDB and G-OLA". All of you are invited to join this session