# Mongo - Performance

## Lesson Objectives
1. Explain indexes
1. Explain text indexes
1. Explain replication
1. Explain sharding

## Explain indexes
1. `db.employees.ensureIndex({name: 1});`
1. `db.employees.dropIndex({name: 1});`
1. `db.employees.ensureIndex({name: 1}, {unique: true});`
1. indexes on embedded fields
1. indexes on arrays
1. `db.employees.ensureIndex({name: 1, salary: -1});`

## Explain text indexes
1. `db.articles.createIndex({ subject : "text", content : "text" })`
1. drop text index
	- `db.articles.getIndexes()`
	- `db.articles.dropIndex('index_name')`
1. `db.articles.find( { $text: { $search: "coffee" } } )`
1. `db.articles.find( { $text: { $search: "leche", $language: "es" } } )`
	- stop words (a, the, and, etc)
1. `db.articles.find( { $text: { $search: "bake coffee cake" } } )`
1. `db.articles.find( { $text: { $search: "\"coffee cake\"" } } )`
1. `db.articles.find( { $text: { $search: "bake coffee -cake" } } )`
1. `db.articles.find( { $text: { $search: "cake" } }, { score: { $meta: "textScore" } } )`
```
db.articles.find(
   { $text: { $search: "cake" } },
   { score: { $meta: "textScore" } }
).sort( { score: { $meta: "textScore" } } )
```

## Explain replication
1. Writes sent to secondary DBs asynchonously
1. Reads can happen on secondaries
	- although data may be stale
1. If primary goes down, a secondary is chosen to be new primary

## Explain sharding
1. split data across multiple servers