DSG Seminar - Twitter Heron in PracticeExport this event to calendar

Tuesday, August 23, 2016 11:29 AM EDT
Speaker: Karthik Ramasamy, Twitter
Abstract:

Twitter generates billions and billions of events per day. Analyzing these events in real time presents a massive challenge. Twitter designed and deployed a new streaming system called Heron. Heron has been in production nearly 2 years and is widely used by several teams for diverse use cases. In this talk, I will describe Heron in detail and share our operating experiences and challenges of running Heron at scale.

Bio:

Karthik is the engineering manager and technical lead for Real Time Analytics at Twitter. He is the co-creator of Heron and has more than two decades of experience working in parallel databases, big data infrastructure and networking. He cofounded Locomatix, a company that specializes in real time streaming processing on Hadoop and Cassandra using SQL that was acquired by Twitter. Before Locomatix, he had a brief stint with Greenplum where he worked on parallel query scheduling. Greenplum was eventually acquired by EMC for more than $300M. Prior to Greenplum, Karthik was at Juniper Networks where he designed and delivered platforms, protocols, databases and high availability solutions for network routers that are widely deployed in the Internet. Before joining Juniper at University of Wisconsin, he worked extensively in parallel database systems, query processing, scale out technologies, storage engine and online analytical systems. Several of these research were spun as a company later acquired by Teradata. He is the author of several publications, patents and one of the best selling book “Network Routing: Algorithms, Protocols and Architectures.” He has a Ph.D. in Computer Science from UW Madison with a focus on databases.

Location 
DC - William G. Davis Computer Research Centre
Room 1304
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

S M T W T F S
27
28
29
30
31
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
  1. 2024 (13)
    1. December (1)
    2. October (3)
    3. June (1)
    4. May (1)
    5. April (1)
    6. March (5)
    7. February (1)
  2. 2023 (13)
    1. December (2)
    2. October (1)
    3. September (2)
    4. August (2)
    5. May (3)
    6. April (1)
    7. February (1)
    8. January (1)
  3. 2022 (6)
  4. 2021 (8)
  5. 2020 (6)
  6. 2019 (27)
  7. 2018 (26)
  8. 2017 (15)
  9. 2016 (25)
  10. 2015 (19)
  11. 2014 (34)