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César Jiménez cesarjimenez

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  • Madrid, Spain
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@terrancesnyder
terrancesnyder / kafka-consumer-example.java
Last active October 15, 2015 11:03
Example of processing Kafka messages using JQuery like deferred / promise for cleaner async code.
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import org.apache.avro.io.BinaryDecoder;
@terrancesnyder
terrancesnyder / kafka-consumer.java
Created February 8, 2014 16:12
Simple example of publishing avro messages to Kafka.
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import org.apache.avro.io.BinaryDecoder;
import org.apache.avro.io.BinaryEncoder;
import org.apache.avro.io.DecoderFactory;
@debasishg
debasishg / gist:8172796
Last active July 5, 2024 11:53
A collection of links for streaming algorithms and data structures

General Background and Overview

  1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  2. Models and Issues in Data Stream Systems
  3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t
@henrik
henrik / tmux_cheatsheet.markdown
Created March 3, 2012 19:47
tmux cheatsheet

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name: