2014
Pluralsight
Nuri Halperin
2:26
English

When it comes to large scale data analysis, NoSQL databases may pose unique challenges - especially with reporting and aggregation. In this course, you will learn how to go beyond simple queries against collections. We will cover key techniques and strategies for digging up and aggregating data in a Big Data world using MongoDB.

Introduction
6m 41s
Introduction 2m 14s
Limitations of find() 2m 31s
Aggregation Choices 1m 55s
Getting Started with the Aggregation Framework
9m 13s
Statefulness 1m 41s
Pipeline Architecture 2m 22s
$group 0m 44s
$unwind 0m 49s
$project 0m 43s
$limit 0m 15s
$skip 0m 9s
$sort 0m 15s
$match 0m 48s
$geoNear 1m 8s
Summary 0m 14s
The $group Pipeline Operator
24m 36s
Introduction 1m 6s
Simple $group 1m 59s
$min $max $avg 1m 48s
Group by Field 1m 20s
Key Rules 0m 35s
Value Rules 1m 26s
Value-Of-Field 0m 58s
Field Name 1m 44s
Arrays and Sets 0m 27s
$addToSet 1m 16s
$push 2m 20s
$first 1m 23s
$last 0m 53s
Order Needed 3m 1s
Command behind aggregate() 1m 46s
Result Structure 0m 17s
Limitations 1m 46s
Summary 0m 22s
Document Selection
18m 16s
Introduction 0m 25s
$match 1m 30s
$match and Arrays 0m 18s
Compound $match 0m 54s
$match for Efficiency 1m 6s
$sort 1m 33s
$sort and Indexes 1m 57s
$limit 2m 42s
$skip 1m 33s
Outliers 0m 37s
Paging 3m 38s
Paging Cost 1m 35s
Summary 0m 22s
Shaping Documents
37m 22s
Introduction 1m 24s
Shaping Needs 1m 25s
$unwind 3m 35s
Thinking Pipeline 1m 56s
$project 0m 49s
Field Selection 2m 28s
Un-Project _id 1m 54s
Field Renaming 1m 32s
Computation 1m 54s
String Functions 2m 45s
Date Functions 1m 30s
Compound Conditional 2m 59s
$ifNull 1m 36s
Building Blocks 1m 21s
Creating Sub-Document 1m 59s
Complex Aggregation 1m 0s
Complex Scenario 0m 34s
Multiple Step Demo 6m 3s
Summary 0m 28s
Other Operators
3m 21s
Introduction 0m 29s
Boolean Operators 0m 38s
Comparison Operators 0m 39s
Arithmetic Operators 0m 10s
String Operators 0m 22s
Date Operators 0m 9s
Conditional Operators 0m 32s
Summary 0m 18s
Performance (Aggregate)
6m 45s
Introduction 0m 37s
Key Principals 0m 21s
Thrift 1m 4s
Rules of Thumb 1m 1s
$match Early 0m 13s
$project Trim 0m 21s
Index Awareness 0m 25s
$sort Early 0m 42s
$sort-$limit Pair 0m 38s
$skip-$limit 0m 10s
$project Optimization 0m 14s
Optimization Cycle 0m 34s
Summary 0m 20s
Map/Reduce
17m 20s
Introduction 0m 34s
Working on Big Data 0m 40s
What is Map/Reduce? 0m 39s
Map 0m 28s
Reduce 0m 18s
The Process 1m 29s
Distributed Work 1m 14s
Flexibility 0m 47s
Basic Syntax 0m 45s
Map Basics 2m 7s
Reduce Basics 3m 21s
Finalize 1m 1s
Demo 3m 29s
Summary 0m 22s
Map/Reduce - Digging Deeper
23m 10s
Introduction 0m 7s
Output Options 2m 31s
Replace 2m 28s
Merge 0m 49s
Reduce 1m 1s
Finalize 1m 57s
Result Type 0m 50s
mapReduce for Ops 1m 9s
Complex Scenario 0m 50s
Mapping for Book 0m 38s
Reducing for Book 1m 3s
Running mapReduce on Book 0m 28s
The Author Collection 0m 18s
Mapping for Author 0m 52s
Reduce for Author 0m 57s
Running mapReduce on Author 0m 25s
Idempotency 0m 40s
Other Scenarios 1m 10s
Usage Considerations 4m 1s
Summary 0m 25s
Course Summary 0m 21s


pluralsight.com/courses/mongodb-big-data-reporting

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