Mongodb官方文档学习（初级篇）

特性
- 一种文档数据库（BSON documents）
- 高性能、丰富的查询语言、高可用、横向扩展、支持多存储引擎
Shell（js接口）
- Date：
  - Date()，返回当前时间的String
  - new Date()，返回Date，通过ISODate()的包装器
  - ISODate()，ISODate("2012-12-19T06:01:17.171Z")
- 检查类型：mydoc._id instanceof ObjectId
- show dbs，use <db>,show users
- $gt、$ gte（大于等于）、 $lt、$ lte

CRUD操作

插入
- collection 不存在会自动创建
- 插入无_id字段时会自动创建
- db.collection.insertOne() ：db. users. insertOne({name: "sue",age: 26,status: "pending"}
- db.collection.insertMany() ：
查找：db.collection.find()
- db.inventory.find( { status: "D" } )
- 嵌入文档查询条件：db.inventory.find( { "size.uom": "in" } )
- 数组
  - db.inventory.find( { tags: ["red", "blank"] } )，包含
  - db.inventory.find( { tags: { $all: ["red", "blank"] } } )，都包含且没有其他的元素
- 返回值：db.inventory.find( { status: "A" }, { item: 1, status: 1, _id: 0 } )，等同于SELECT item, status from inventory WHERE status = "A"
- sort、skip、limit、comunt

db.inventory.find( { status: { $in: [ "A", "D" ] } } )
db.inventory.find( {
 status: "A",
 $or: [ { qty: { $lt: 30 } }, { item: /^p/ } ]
} )
db.inventory.find( { dim_cm: { $gt: 15, $lt: 20 } } )

更新
- db.collection.updateOne()
- db.collection.updateMany()
- db.collection.replaceOne()
- 其他能起到更新效果的方法：
  - db.collection.findOneAndReplace().
  - db.collection.findOneAndUpdate().
  - db.collection.findAndModify().
  - db.collection.save().
  - db.collection.bulkWrite().
删除
- db.collection.deleteOne()
- db.collection.deleteMany()
- 其他方法：
  - db.collection.findOneAndDelete().
  - db.collection.findAndModify().
  - db.collection.bulkWrite().

db.inventory.insertMany([
{ item: "journal", qty: 25, tags: ["blank", "red"], size: { h: 14, w: 21, uom:     "cm" } },
{ item: "mat", qty: 85, tags: ["gray"], size: { h: 27.9, w: 35.5, uom: "cm" } },
{ item: "mousepad", qty: 25, tags: ["gel", "blue"], size: { h: 19, w: 22.85,     uom: "cm" } }
])

对比

SQL Terms/Concepts	MongoDB Terms/Concepts
database	database
table	collection
row	document or BSON document
column	field
index	index
table joins	$lookup, embedded documents
primary key（Specify any unique column or column combination as primary key.）	primary key （In MongoDB, the primary key is automatically set to the _id field.）
aggregation (e.g. group by)	aggregation pipeline
transactions	transactions

文本搜索
- 文本索引：db.stores.createIndex( { name: "text", description: "text" } )
- 搜索：db.stores.find( { $text: {$ search: "java coffee shop" } } )
- 聚合管道的文本搜索
```
db.articles.aggregate(
   [
     { $match: { $text: { $search: "cake" } } },
     { $group: { _id: null, views: { $sum: "$views" } } }
   ]
)
```

地理位置（GEO）

GeoJSON Point

location: {
      type: "Point",
      coordinates: [-73.856077, 40.848447]
}

聚合（Aggregation,这个可以点进去看一下）

管道聚合（Aggregation Pipeline）

db.aggregate( [ { <stage> }, ... ] )
Operator Expressions
- Arithmetic Expression Operators: $abs,$ add, $ln,$ mod,$power……
- Array Expression Operators: $in,$ range,$size……
- Boolean Expression Operators： $and,$ not,$or
- Comparison Expression Operators: $cmp,$ eq(equal), $gt,$ gte, $lt,$ lte,$ne(not equal)
- Conditional Expression Operators
- Date Expression Operators
比较

SQL Terms, Functions, and Concepts	MongoDB Aggregation Operators
WHERE	$match
GROUP BY	$group
HAVING	$match
SELECT	$project
ORDER BY	$sort
LIMIT	$limit
SUM()	$sum
COUNT()	$sum,$ sortByCount
join	$lookup

示例

        
        {//orders
          cust_id: "abc123",
          ord_date: ISODate("2012-11-02T17:04:11.102Z"),
          status: 'A',
          price: 50,
          items: [ { sku: "xxx", qty: 25, price: 1 },
                   { sku: "yyy", qty: 25, price: 1 } ]
        }
        SELECT COUNT(*) AS count FROM orders
        db.orders.aggregate( [
           {
             $group: {
                _id: null,
                count: { $sum: 1 }
             }
           }
        ] )
        
        SELECT cust_id,
        SUM(price) as total
        FROM orders
        WHERE status = 'A'
        GROUP BY cust_id
        db.orders.aggregate( [
         { $match: { status: 'A' } },
         {
         $group: {
          _id: "$cust_id",
         total: { $sum: "$price" }
         }
         },
         { $match: { total: { $gt: 250 } } }
        ] )

map-reduce

    //案例：计算每个单位订单中数量的平均值(Calculate Order and Total Quantity with Average Quantity Per Item)
    {// collection orders
     _id: ObjectId("50a8240b927d5d8b5891743c"),
     cust_id: "abc123",
     ord_date: new Date("Oct 04, 2012"),
     status: 'A',
     price: 25,
     items: [ { sku: "mmm", qty: 5, price: 2.5 },
              { sku: "nnn", qty: 5, price: 2.5 } ]
    }
    //提交（key，value），对每个items数组提取sku作为key，qty作为value数组的一个字段,count初始化为1
    var mapFunction2 = function() {
                       for (var idx = 0; idx < this.items.length; idx++) {
                           var key = this.items[idx].sku;
                           var value = {
                                         count: 1,
                                         qty: this.items[idx].qty
                                       };
                           emit(key, value);
                       }
                    };
    // 对每个key，合并value               
    var reduceFunction2 = function(keySKU, countObjVals) {
                     reducedVal = { count: 0, qty: 0 };

                     for (var idx = 0; idx < countObjVals.length; idx++) {
                         reducedVal.count += countObjVals[idx].count;
                         reducedVal.qty += countObjVals[idx].qty;
                     }

                     return reducedVal;
                  };
    // 对每个key，计算订单中数量的平均值              
    var finalizeFunction2 = function (key, reducedVal) {

                       reducedVal.avg = reducedVal.qty/reducedVal.count;

                       return reducedVal;

                    };
    // query 条件                
    db.orders.mapReduce( mapFunction2,
                     reduceFunction2,
                     {
                       out: { merge: "map_reduce_example" },
                       query: { ord_date:
                                  { $gt: new Date('01/01/2012') }
                              },
                       finalize: finalizeFunction2
                     }
                   )