MongoDB uses B-trees to represent indexes internally and recommends indexing keys that are frequently used in WHERE clauses, such as unique user names. Indexes can be single or multi-key and are created using the ensureIndex method. While indexes improve query performance, over-indexing can reduce performance of insert, update and delete operations. It is important to consider the tradeoff between faster queries and slower write operations when choosing indexes.

1. MongoDB Indexes
Indexing explained.

2. Indexing.
• MongoDB represents indexes internally as B-trees
• Consider indexing keys that are used frequently in WHERE clauses.
e.g > db.user.find("uName":”anish”) uName or user name is unique and not to changed
frequently ideal candidate for Index
To create the index, use the ensureIndex method:
One Key Index
db.user.ensureIndex({“uName" : 1})
“1” refer as Direction
Two key Index
db.ensureIndex({“uName" : 1, “emailId" : 1})
Do not index Keys that are modified frequently
e.g Key containing
temp_address
remarks

3. Indexing Caution
Too Much of Indexing will result in poor
performance in query
When choosing to index a key, consider whether
the performance gain for queries is worth the
performance loss for INSERTs, UPDATEs, and
DELETEs and the use of the space required to
store the index. You might want to experiment
by comparing the processing times of the quries
with and without indexes.

4. More Advanced queries
http://docs.mongodb.org/manual/reference/op
erators/#AdvancedQueries-

5. Thanks for Watching
feedback
appreciated………………
…………