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1
Intro
2
MapReduce on Hadoop
3
The Market
4
Data Centers
5
RAID Array
6
Distributed Hashmap
7
Memory Model
8
Reliable Computation
9
Fork Join
10
Fork Joint
11
Task Split
12
Task Death
13
Moron
14
REST API
15
Parallel Java
16
HDFS
17
Distributed KBstore
18
Distributed forkjoin
19
Programming model
20
Appendonly
Description:
Explore the intersection of big data and small computers in this 21-minute Java conference talk. Delve into topics such as MapReduce on Hadoop, data centers, RAID arrays, distributed hashmaps, and memory models. Learn about reliable computation techniques, fork-join parallelism, task splitting, and distributed key-value stores. Gain insights into programming models for big data processing, including parallel Java implementations, HDFS, and append-only data structures. Discover how to leverage small computers for handling large-scale data challenges and optimize your approach to big data processing.

Big Data Processing on Small Computers

Java
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