Mudit emptyr1

Jennifer Zhao | SQL Problems Collection | 2018-02-22 22:14:27

Comments I
- Calculate the average comments for the users with >= 2 posts, and each post has comments greater or equal to 40
Comments II
- What is the distribution of comments?
Now what if content_type becomes {comment, video, photo, article}，what is the comment distribution for each content type?

##Google Interview Questions: Product Marketing Manager

Why do you want to join Google? -- Because I want to create tools for others to learn, for free. I didn't have a lot of money when growing up so I didn't get access to the same books, computers and resources that others had which caused money, I want to help ensure that others can learn on the same playing field regardless of their families wealth status or location.
What do you know about Google’s product and technology? -- A lot actually, I am a beta tester for numerous products, I use most of the Google tools such as: Search, Gmaill, Drive, Reader, Calendar, G+, YouTube, Web Master Tools, Keyword tools, Analytics etc.
If you are Product Manager for Google’s Adwords, how do you plan to market this?
What would you say during an AdWords or AdSense product seminar?
Who are Google’s competitors, and how does Google compete with them? -- Google competes on numerous fields: --- Search: Baidu, Bing, Duck Duck Go

The introduction to Reactive Programming you've been missing

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.

General Background and Overview

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.
Models and Issues in Data Stream Systems
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
Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
[Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

Intro

The plan is to create a pair of executables (ngrok and ngrokd) that are connected with a self-signed SSL cert. Since the client and server executables are paired, you won't be able to use any other ngrok to connect to this ngrokd, and vice versa.

DNS

Add two DNS records: one for the base domain and one for the wildcard domain. For example, if your base domain is domain.com, you'll need a record for that and for *.domain.com.

Different Operating Systems

MySQL

Getting started:

	// This example shows how to use row_number and rank to create
	// a dataframe of precipitation values associated with a zip and date
	// from the closest NOAA station

	import org.apache.spark.sql.expressions.Window
	import org.apache.spark.sql.functions._

	// mocked NOAA weather station data
	case class noaaData(zip:String,station:String,date:Long,value:String=null,distance:Int)
	val t = Seq(

	package main

	import (
	"fmt"
	"time"
	)

	// Suggestions from golang-nuts
	// http://play.golang.org/p/Ctg3_AQisl

	# List unique values in a DataFrame column
	pd.unique(df.column_name.ravel())

	# Convert Series datatype to numeric, getting rid of any non-numeric values
	df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

	# Grab DataFrame rows where column has certain values
	valuelist = ['value1', 'value2', 'value3']
	df = df[df.column.isin(valuelist)]

	// Use Gists to store code you would like to remember later on
	console.log(window); // log the "window" object to the console