walteryu

// jQuery script for validating user input
$(document).ready(function () {
    $('#random-user').append("Form submitted successfully!");

    $('#random-user').validate({
        // initialize jquery validation plugin
        rules: {
            count: {
                required: true
            },

walteryu

#!/bin/bash

# Download MySQL connector, store in working folder then unpack for use:
tar zxvf mysql-connector-java-5.1.31.tar.gz

# Call PySpark with MySQL connector:
pyspark --driver-class-path mysql-connector-java-5.1.47-bin.jar

walteryu

# CSCI E-63 HW3 - Problem 3
# Author: Walter Yu
# Description: PySpark script to connect to MySQL database, register table and display row count.

# Create context and connect to MySQL:
sqlContext= SQLContext(sc)
dfm = sqlc.read.format("jdbc").option("url","jdbc:mysql://localhost/retail_db").option("driver","com.mysql.jdbc.Driver").option("dbtable","departments").option("user","xxxxx").option("password","xxxxx").load()

# Verify schema, create view and display row count:
dfm.printSchema()

walteryu

'''
Author: Walter Yu
Course: CSCI E-63, Fall 2018
Assignment: HW3, Problem 2
References:
Slide 46 & 47, Lecture 3 Notes
SparkContext Tutorial:https://www.tutorialspoint.com/pyspark/pyspark_sparkcontext.htm
'''
from pyspark import SparkContext, SparkConf
from pyspark.sql import SQLContext, Row, SparkSession

walteryu

#!/bin/bash

# CSCI E63 HW4 - Walter Yu, Fall 2018
# Script commands to complete HW4

# P1 - Compress data file for trasnfer into VM:
tar -zcvf retail-data.tar.gz ../e63-hw4-data-oreilly/data/retail-data

# P1 - Extract data file within VM:
tar -zxvf prog-1-jan-2005.tar.gz -C /tmp

walteryu

/*
CSCI E63 HW5 - Walter Yu, Fall 2018
Script commands to complete HW5
*/

-- Q1: Create tables:
create table stations(
  stations_id    int(11)       ,
  name           varchar(64)   ,
  latitude       decimal(11)   ,

walteryu

#!/bin/bash

# CSCI E63 HW5 - Walter Yu, Fall 2018
# Script commands to complete HW5

# P1 - Compress data file for trasnfer into VM:
tar -zcvf retail-data.tar.gz ../e63-hw4-data-oreilly/data/retail-data

# P1 - Extract data file within VM:
tar -zxvf prog-1-jan-2005.tar.gz -C /tmp

walteryu

from pyspark.sql import SparkSession
from pyspark.sql.functions import explode
from pyspark.sql.functions import split

spark = SparkSession.builder.appName("StructuredNetworkWordCount").getOrCreate()

lines = spark.readStream.format("socket").option("host", "localhost") \
    .option("port", 9999).load()

# Split the lines into words