Vaquar Khan vaquarkhan

Sessions

Code	Title	Duration	Link
Keynote	Andy Jassy Keynote Announcement Recap	0:01	https://www.youtube.com/watch?v=TZCxKAM2GtQ
Keynote	AWS re:Invent 2016 Keynote: Andy Jassy	2:22	https://www.youtube.com/watch?v=8RrbUyw9uSg
Keynote	AWS re:Invent 2016 Keynote: Werner Vogels	2:16	https://www.youtube.com/watch?v=ZDScBNahsL4
Keynote	[Tuesday Night Live with Jame

Resources

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

import boto3

client = boto3.client('glue')

response = client.create_crawler(
    Name='SalesCSVCrawler',
    Role='AWSGlueServiceRoleDefault',
    DatabaseName='sales-cvs',
    Description='Crawler for generated Sales schema',

Cassandra Notes

Introduction

Apache Cassandra is an open source, distributed database management system. Cassandra is designed to handle large amounts of data across many commodity servers. Cassandra uses a query language named CQL.

Cassandra's data model is a partitioned row store; Cassandra combines elements of key-value stores and tabular/columnar databases. Like a relational database, Cassandra stores data in tables, called column families, that have defined columns and associated data types. Each row in a column family is uniquely identified by a key. Each row has multiple columns, each of which has a timestamp, name, and value. Unlike a relational database, each row in a column family does not need to have the same set of columns. At any time, a column may be added to one or more rows. If this explanation is unclear, you might think of column families instead as sets of key-value pairs, in which the values are nested sets of key-value pairs.

The following depicts two rows of a column-family fro

	import org.apache.spark.graphx._
	import org.apache.spark.rdd.RDD

	case class Peep(name: String, age: Int)

	val vertexArray = Array(
	(1L, Peep("Kim", 23)),
	(2L, Peep("Pat", 31)),
	(3L, Peep("Chris", 52)),
	(4L, Peep("Kelly", 39)),

	// load error messages from a log into memory
	// then interactively search for various patterns

	// base RDD
	val lines = sc.textFile("log.txt")

	// transformed RDDs
	val errors = lines.filter(_.startsWith("ERROR"))
	val messages = errors.map(_.split("\t")).map(r => r(1))
	messages.cache()

	import boto3

	client = boto3.client(
	'emr',
	region_name='eu-west-1'
	)

	cmd = "hadoop jar /usr/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar wordcount file:///etc/services /output"

	emrcluster = client.run_job_flow(

	package com.issue.chaos.monkey.demo;

	import org.springframework.boot.SpringApplication;
	import org.springframework.boot.autoconfigure.SpringBootApplication;

	@SpringBootApplication
	public class DemoApplication {

	public static void main(String[] args) {
	SpringApplication.run(DemoApplication.class, args);

	################################### Keras2DML: Parallely training neural network with SystemML#######################################
	import tensorflow as tf
	import keras
	from keras.models import Sequential
	from keras.layers import Input, Dense, Conv1D, Conv2D, MaxPooling2D, Dropout,Flatten
	from keras import backend as K
	from keras.models import Model
	import numpy as np
	import matplotlib.pyplot as plt