MongoDB Hadoop DC
8 likes1,348 views
The document discusses MongoDB, an open-source, high-performance, schema-free document-oriented database, emphasizing its flexibility and ease of development. It illustrates usage examples for creating and querying posts in a blog application while addressing its strengths in web applications and scalability, and its limitations in highly transactional environments. Additionally, it mentions advanced features like aggregation, sharding, and indexing, providing a hands-on guide to utilizing various functions within MongoDB.
![Post
{author: “mike”,
date: new Date(),
text: “my blog post...”,
tags: [“mongodb”, “dc”, “hadoop”]}](https://image.slidesharecdn.com/hadoopdc-091019090017-phpapp01/85/MongoDB-Hadoop-DC-13-320.jpg)
![New post
post = {author: “mike”,
date: new Date(),
text: “my blog post...”,
tags: [“mongodb”, “dc”, “hadoop”]}
db.posts.save(post)](https://image.slidesharecdn.com/hadoopdc-091019090017-phpapp01/85/MongoDB-Hadoop-DC-15-320.jpg)
![Migration: adding titles
• Easy - just start adding them:
post = {author: “mike”,
date: new Date(),
text: “another blog post...”,
tags: [“meetup”, “hadoop”],
title: “Review from Hadoop DC”}
post_id = db.posts.save(post)](https://image.slidesharecdn.com/hadoopdc-091019090017-phpapp01/85/MongoDB-Hadoop-DC-31-320.jpg)
MongoDB Hadoop DC
- 4. Schema-free • Loosening constraints - added flexibility • Dynamically typed languages • Migrations
- 5. Dynamic queries • Administration • Ease of development • Familiarity
- 7. Replication
- 9. Many supported platforms / languages
- 10. Good at • The web • Caching • High volume data • Scalability
- 11. Less good at • Highly transactional • Ad-hoc business intelligence • Problems that require SQL
- 13. Post {author: “mike”, date: new Date(), text: “my blog post...”, tags: [“mongodb”, “dc”, “hadoop”]}
- 14. Comment {author: “eliot”, date: new Date(), text: “great post!”}
- 15. New post post = {author: “mike”, date: new Date(), text: “my blog post...”, tags: [“mongodb”, “dc”, “hadoop”]} db.posts.save(post)
- 16. Embedding a comment c = {author: “eliot”, date: new Date(), text: “great post!”} db.posts.update({_id: post._id}, {$push: {comments: c}})
- 17. Posts by author db.posts.find({author: “mike”})
- 18. Last 10 posts db.posts.find() .sort({date: -1}) .limit(10)
- 19. Posts in the last week last_week = new Date(2009, 9, 9) db.posts.find({date: {$gt: last_week}})
- 20. Sharding
- 21. Terminology • Shard key • Chunk • Range of the value space • (collection, key, min_val, max_val) • Shard • Single node (or replica pair) • Responsible for set of chunks
- 24. Other cool stuff • Aggregation and map reduce • Capped collections • Unique indexes • Mongo shell • GridFS
- 25. • Download MongoDB http://www.mongodb.org • Try it out • Let us know what you think
- 26. • http://www.mongodb.org • irc.freenode.net#mongodb • mongodb-user on google groups • @mongodb, @mdirolf • mike@10gen.com • http://www.slideshare.net/mdirolf
- 27. Posts ending with ‘Hadoop’ db.posts.find({text: /hadoop$/})
- 28. Posts with a tag db.posts.find({tag: “mongodb”}) ... and fast db.posts.ensureIndex({tag: 1})
- 30. Basic paging page = 2 page_size = 15 db.posts.find().limit(page_size) .skip(page * page_size)
- 31. Migration: adding titles • Easy - just start adding them: post = {author: “mike”, date: new Date(), text: “another blog post...”, tags: [“meetup”, “hadoop”], title: “Review from Hadoop DC”} post_id = db.posts.save(post)
- 32. Advanced queries • $gt, $lt, $gte, $lte, $ne, $all, $in, $nin • where() db.posts.find({$where: “this.author == ‘mike’”})