Google Big Table Deep Dive and Spark SQL Acceleration with Apache Ignite (Chicago)
We united with Chicago Data Engineering
Please bring an ID to get into the building.
6:00pm - 6:30pm: Networking and snacks
6:30pm - 7:00pm: "How to Speed Up Spark SQL With In-Memory Computing Stack?" talk by Denis Magda
7:00pm - 7:30pm: "Google Big Table - Store data at scale" talk by Piyush Sanghi
7:30pm - 8:00pm: Q/A with Speakers and
How to find us
McKinsey & Company
300 E Randolph St #3100 · Chicago, IL
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Talk #1: How to Speed Up Spark SQL With In-Memory Computing Stack?
With Spark SQL based on the Catalyst optimizer, we can query and join various data sources, including Hive, relational databases, Avro, and Parquet.
This talk aims to explain how Apache Ignite’s in-memory store and internal SQL engine were integrated into the Catalyst optimizer to accelerate real-time analytics workloads with a highly-
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Talk #2: Google Big Table - Store data at scale
With massive speeds at which data are collected, we need new ways of persisting data at scale. Enter Google Big Table, which provides sub 10ms latency and scales to peta-bytes. We will look at how Google Big Table scaling works and when to use it.