Some notes about the MONGO index

This article mainly introduced about the MONGO index of some of the notes, has a certain reference value, now share to everyone, the need for friends can refer to

Index usage Scenarios

Excellent: Faster query speed

Inferior: Add and delete will incur additional overhead, occupy space

Tips: Returns more than half of the data in a collection, with high efficiency for full table scans

Index base

Basic operations

View index: Db.test.getIndexes ()

CREATE INDEX: Db.test.ensureIndex ({"username": 1},{"Background": True, "name": "Index_test_name"})//There is a large amount of data available for background execution without blocking

Delete index: Db.test.dropIndex ({"username": 1})

View index Size: db.test.totalIndexSize ()

Property

Index Order:

1 is the positive sequence, 1 is reverse order

Order of attention in composite indexes (Id:1, age:-1)

Indexed properties:

• Uniqueness

Db.test.ensureIndex ({x:1,y:1},{unique:true})

• Sparse Nature

Db.test.ensureIndexx ({},{sparse:true/false}) is not sparse (default): 1. You can insert data that does not exist in the indexed field, NULL; 2. Can filter non-existent fields: Db.test.find ({m:{$exist: ture}) Sparse:

Optimization Analysis method

• Explain

  Learn how the system handles requests

Cursor  return cursor type (basiccursor or btreecursor) nscanned  Number of documents scanned n number of documents returned Millis  time (ms) Indexbounds  Index used

• Hint

  Force an index to be used

Db.test.find ({"Age": +}). Hint ({"name": 1, "Age": 1})//. Hint (name_1_age_1)

• Profile

  Set the log level to record slow queries

Tips

1. Automatic adjustment of Query condition order

2. Can be a prefix-type regular expression hit index (/^z/)

3. Indexing keys that require a large number of sort to prevent all data from being loaded into memory

4. $ne, $nin do not use indexes

Type of index

• _ID Index

• Single-Touch indexing

• Multi-Key indexing

• Composite Index

• Expired Index

• Full-Text Indexing

• Location Index

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