Join Dan Sullivan for an in-depth discussion in this video Index data with document databases, part of Advanced NoSQL for Data Science.
- [Instructor] We're continuing from where we left off…in our last video.…Next, I want to import the time package…because I want to do a little bit of timing here.…What I'd like to do is show how to create an index…on a MongoDB collection.…Now the first thing I want to do is…show you how long it takes to query something…without an index, so I'm going to…create a variable called start…for keeping track of time,…and I'm going to call the time function…in the time package, and then I'm going to…add a few more items to this block.…I want to say, get a list of everybody who's age 50,…and to do that I'm going to start with my collection…and I'm going to issue a find command…and I'm going to look at age equal to 50,…and then I'm going to compute an end time,…and again, I'm just going to take the time from the machine…and then I want to print out the difference between…the start and the end time.…
Okay, I missed a colon in my find query…so I'm going to insert that and run this again.…Ah, took about .0002 seconds.…Now let's create an index.…
The course begins with an introduction to NoSQL, and then delves into the specifics of document, wide-column, and graph databases. Learn key details for performing data preparation, exploration, and extraction for each type of NoSQL database. Review case studies that show how to use various NoSQL databases with popular data science tools, including the document database MongoDB, the wide-column database Cassandra, and the graph database Neo4j.
- NoSQL compared to traditional relational databases
- Performing common data science tasks
- Preparing data with document databases
- Manipulating data in NoSQL
- Preparing, exploring, extracting, and model building
- Working with document, wide-column, and graph databases
- Reviewing case studies using MongoDB, Cassandra, and Neo4j
Skill Level Advanced
1. Why NoSQL?
Types of NoSQL databases2m 20s
2. Perform Common Data Science Tasks with NoSQL Databases
3. Document Databases for Data Science
4. Wide-Column Databases for Data Science
5. Graph Databases for Data Science
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