1. 1 More MongoDB: Ch 3- 8, plus a little Hadoop CSSE 533 Week 2, Spring, 2015

2. 2 Topics this week MongoDB – continued: Ch 3 - Creating, updating and deleting documents Ch 4 – Querying Ch 5 – Indexing Ch 6 – Special index and collection types Ch 7 – Aggregation and MapReduce Ch 8 – Application design Intro to Hadoop (from Data Science book) See the reading on Moodle.

3. 3 Ch 3 - Creating, updating and deleting documents Inserting and saving documents How fast? Removing documents Updating documents The read / change / rewrite cycle

4. 4 Ch 3 – Pages to look at P 31 – bottom : You can time how fast things operate. Just define a function with time capture before and after what you are doing. Pp 31 – 40: You can read and replace whole documents, or not. P 34: Can also modify, like incrementing counters. P 37: “$inc” is similar to “$set,” but is designed for incrementing (and decrementing) numbers… There are special conditions and cautions on every one of these features! P 41: “Array manipulation becomes a little trickier when we have multiple values in an array and want to modify some of them…” Ditto Which brings up my idea of your doing some rather loosely defined homework to gain confidence in using all these commands, etc. P 47: Updating multiple documents P 50: Setting a write concern

5. 5 Ch 4 – Querying Everything about “find” Many criteria Type-specific queries Using “$where” Cursors Database commands

6. 6 Ch 4 – Pages to look at P 57: Conditional semantics P 58: Null behavior P 61: $slice operator P 65: $where queries P 66: Security issues P 67: Cursors P 73: The warning about “Getting consistent results”! P 75: Database commands

7. 7 Ch 5 – Indexing All the variations Like compound indexes Query optimization Issues Index types Changing indexes?

8. 8 Ch 5 – Pages to look at First chapter in “Designing your application.” Pp 81-4: Basically, indexes are like in RDBMS’s. Friend to reads, enemies to writes. P 91: Cautions about efficiency of compound indexes. P 98: Using explain() and hint() P 102: The query optimizer P 102: When not to index

9. 9 Ch 6 – Special index and collection types Capped collections Time-to-live indexes Full-text indexes Geospatial indexing Storing files with GridFS

10. 10 Ch 6 – Pages to look at P 109: Capped collections – like for logs P 113: Tailable cursors – run on new data! P 115: Full-text indexes – look dangerous

11. 11 Ch 7 – Aggregation and MapReduce The aggregation framework Pipeline operations MapReduce Aggregation commands

12. 12 Ch 7 – Pages to look at P 127: The aggregation framework P 129: Pipeline operations P 134: A projection example P 141: Example 1 P 143: Example 2 P 150: Using a finalizer

13. 13 Ch 8 – Application design Normalization vs denormalization Optimization for data manipulation Planning out databases and collections Managing consistency Migrating schemas When not to use MongoDB !

14. 14 Ch 8 – Pages to look at P 153: How much to normalize? P 157: Cardinality P 158: Friends, followers, and other inconveniences P 159: Wil Wheaton! P 160: Optimizations P 165: When not to use MongoDB