插入操作
在collection中创建documnets, 如果collection不存在,则会自动创建
单条插入: db.collection.insertOne()
批量插入: db.collection.insertMany()
单条数据插入
db.inventory.insertOne(
{ item: "canvas", qty: 100, tags: ["cotton"], size: { h: 28, w: 35.5, uom: "cm" } }
)
多条数据插入
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" } }
])
读取操作
简单查询
db.inventory.find( {} )
VS
SELECT * FROM inventory
条件查询
db.inventory.find( { status: "D" } )
VS
SELECT * FROM inventory WHERE status = "D"
多条件查询
- and
db.inventory.find( { status: "A", qty: { $lt: 30 } } )
db.inventory.find( { $and: [ { status: "A" }, { qty: { $lt: 30 } } ] } )
VS
SELECT * FROM inventory WHERE status = "A" AND qty < 30
- or
db.inventory.find( { $or: [ { status: "A" }, { qty: { $lt: 30 } } ] } )
VS
SELECT * FROM inventory WHERE status = "A" OR qty < 30
- and - or
db.inventory.find( {
status: "A",
$or: [ { qty: { $lt: 30 } }, { item: /^p/ } ]
} )
VS
SELECT * FROM inventory WHERE status = "A" AND ( qty < 30 OR item LIKE "p%")
-
备注:
db.collection.findone()
方法是在db.collection.find()
方法中加入了limit 1
的条件;常用条件表达式:
mongo表达式 常见表示 表达式描述 $gt > 大于 $gte >= 大于等于 $lt < 小于 $lte <= 小于等于
范围查询
db.inventory.find( { status: { $in: [ "A", "D" ] } } )
VS
SELECT * FROM inventory WHERE status in ("A", "D")
模糊查询
db.products.find( { sku: { $regex: /789$/ } } )
VS
SELECT * FROM products WHERE sku like "%789";
联合查询
- union all
db.suppliers.aggregate([ // 当前表
{ $project: { state: 1, _id: 0 } },
{ $unionWith: {
coll: "warehouses", // 需要union的表
pipeline: [ // 需要union的表查询条件
{ $project: { state: 1, _id: 0 } } ]} }
]
)
- left join
db.orders.aggregate([ // 左表
{
$lookup:
{
from: "inventory", // 右表
localField: "item", // 左表关键字
foreignField: "sku", // 右表关键字
as: "inventory_docs" // 右表关联数据别名
}
}
])
分组查询
db.sales.aggregate( [
{
$group: {
_id: null,
count: { $sum: 1 }
}
}
] )
SELECT COUNT(*) AS count FROM sales
db.sales.aggregate(
[
// First Stage
{
$group :
{
_id : "$item",
totalSaleAmount: { $sum: { $multiply: [ "$price", "$quantity" ] } }
}
},
// Second Stage
{
$match: { "totalSaleAmount": { $gte: 100 } }
}
]
)
SELECT item,
Sum(( price * quantity )) AS totalSaleAmount
FROM sales
GROUP BY item
HAVING totalSaleAmount >= 100
db.sales.aggregate([
// First Stage
{
$match : { "date": { $gte: new ISODate("2014-01-01"), $lt: new ISODate("2015-01-01") } }
},
// Second Stage
{
$group : {
_id : { $dateToString: { format: "%Y-%m-%d", date: "$date" } },
totalSaleAmount: { $sum: { $multiply: [ "$price", "$quantity" ] } },
averageQuantity: { $avg: "$quantity" },
count: { $sum: 1 }
}
},
// Third Stage
{
$sort : { totalSaleAmount: -1 }
}
])
SELECT date,
Sum(( price * quantity )) AS totalSaleAmount,
Avg(quantity) AS averageQuantity,
Count(*) AS Count
FROM sales
GROUP BY Date(date)
ORDER BY totalSaleAmount DESC
更新操作
-
单条更新 :
db.collection.updateOne()
- 更新单个文档
db.collection.updateOne(
, , )
$set
$set
修饰符来更新字段
$currentDate
将字段更新为当前时间
db.inventory.updateOne(
{ item: "paper" },
{
$set: { "size.uom": "cm", status: "P" },
$currentDate: { lastModified: true }
}
)
- 更新多个文档
db.inventory.updateMany(
{ "qty": { $lt: 50 } },
{
$set: { "size.uom": "in", status: "P" },
$currentDate: { lastModified: true }
}
)
- 替换文档
替换文档时,只写键值对就可以了,不要更新运算符
db.inventory.replaceOne(
{ item: "paper" },
{ item: "paper", instock: [ { warehouse: "A", qty: 60 }, { warehouse: "B", qty: 40 } ] }
)
- mongodb中的所有写操作都是单个文档级别的原子操作
- _id 字段设置后,将无法更新 _ id 字段的值, 也无法使用具有不同 _id字段值的替换文档替换现有文档
- mongodb会在执行写操作后保留文档字段的顺序。 _id 字段始终时第一个字段
删除操作
-
批量删除 :
db.collection.deleteMany()
- 全量删除
db.inventory.deleteMany({})
- 根据条件删除
db.inventory.deleteMany({ status : "A" })
- 只删除一个
db.inventory.deleteOne( { status: "D" } )
删除方法
db.collection.deleteOne() |
即使多个文档可能与指定过滤器匹配,也最多删除一个与指定过滤器匹配的文档。3.2版中的新功能。 |
db.collection.deleteMany() |
删除所有与指定过滤器匹配的文档。3.2版中的新功能。 |
db.collection.remove() |
删除单个文档或与指定过滤器匹配的所有文档。 |
db.collection.findOneAndDelete() |
提供了一个排序选项。该选项允许删除按指定顺序排序的第一个文档。 |
db.collection.findAndModify() |
提供排序选项。该选项允许删除按指定顺序排序的第一个文档。 |
db.collection.bulkWrite() |
进阶
查询进阶
插入数据源
db.inventory.insertMany( [
{ item: "journal", qty: 25, size: { h: 14, w: 21, uom: "cm" }, status: "A" },
{ item: "notebook", qty: 50, size: { h: 8.5, w: 11, uom: "in" }, status: "A" },
{ item: "paper", qty: 100, size: { h: 8.5, w: 11, uom: "in" }, status: "D" },
{ item: "planner", qty: 75, size: { h: 22.85, w: 30, uom: "cm" }, status: "D" },
{ item: "postcard", qty: 45, size: { h: 10, w: 15.25, uom: "cm" }, status: "A" }
]);
嵌套文档查询
在文档的单个字段上进行查询
查询 size={ h: 14, w: 21, uom: "cm" } 的数据
db.inventory.find( { size: { h: 14, w: 21, uom: "cm" } } )
在文档内的嵌套字段上进行查询
查询size.uom=in (size下的内嵌文档中的uom)的数据
db.inventory.find( { "size.uom": "in" } )
数组查询
- 匹配一个数组
完全匹配模式,普通查询都是完全匹配模式,value必须完全一致
db.inventory.find( { tags: ["red", "blank"] } )
自由匹配模式
$all
,查询出数组中同时包含"red"和 "blank"元素的数据,不管顺序
db.inventory.find( { tags: { $all: ["red", "blank"] } } )
- 根据数组中的元素进行查找(满足一个条件即可)
根据数组中的某一个元素,查询包含该元素的数据
数组元素中还包含 “red” 的数据
db.inventory.find( { tags: "red" } )
数组中至少有一个元素>25 的数据
db.inventory.find( { dim_cm: { $gt: 25 } } )
数组元素中包含 >15或<20 或 15<x<20 的数据
db.inventory.find( { dim_cm: { $gt: 15, $lt: 20 } } )
- 指定数组元素多重条件(满足所有条件)
$elemMatch
指定多个条件, 至少一个元素满足条件 >22且<30
db.inventory.find( { dim_cm: { $elemMatch: { $gt: 22, $lt: 30 } } } )
按照元素索引位置进行查找
查找数组中第二个元素>25 的数据
array.index
数组.元素下标
db.inventory.find( { "dim_cm.1": { $gt: 25 } } )
根据数组元素个数查询
$size
db.inventory.find( { "tags": { $size: 3 } } )
- 查询嵌入式文档数组
嵌入式文档查询上边已经介绍过了
数组查询也已经介绍过了
现在时将两者综合运用
在嵌入式文档数组中的字段上使用查询条件
db.inventory.find( { 'instock.qty': { $lte: 20 } } )
在嵌入式文档数组中的元素索引上使用查询条件
db.inventory.find( { 'instock.0.qty': { $lte: 20 } } )
返回查询的字段
db.inventory.find( { status: "A" }, { item: 1, status: 1 } )
VS
SELECT _id, item, status from inventory WHERE status = "A"
如果不想返回_id
字段,可以将_id:0
db.inventory.find( { status: "A" }, { item: 1, status: 1, _id: 0 } )
想要返回什么字段,字段的值就==1,不想显示什么字段就 ==0
如果全是 1,则全部返回;
有0有1的,返回为1 的
全都是0,返回非0 的其他全部字段
$slice
分片,根据数组下标范围进行数组截取,-1
表示取最后一个数据
db.inventory.find( { status: "A" }, { item: 1, status: 1, instock: { $slice: -1 } } )
查询为空或者字段缺失的数据
db.inventory.insertMany([
{ _id: 1, item: null },
{ _id: 2 }
])
- 平等过滤器,两条数据都会被查出来
db.inventory.find( { item: null } )
- 类型检查
只返回类型为null的数据
$type
db.inventory.find( { item : { $type: 10 } } )
- 类型说明列表
Type | Number | Alias | Notes |
---|---|---|---|
Double | 1 | “double” | |
String | 2 | “string” | |
Object | 3 | “object” | |
Array | 4 | “array” | |
Binary data | 5 | “binData” | |
Undefined | 6 | “undefined” | Deprecated. |
ObjectId | 7 | “objectId” | |
Boolean | 8 | “bool” | |
Date | 9 | “date” | |
Null | 10 | “null” | |
Regular Expression | 11 | “regex” | |
DBPointer | 12 | “dbPointer” | Deprecated. |
JavaScript | 13 | “javascript” | |
Symbol | 14 | “symbol” | Deprecated. |
JavaScript code with scope | 15 | “javascriptWithScope” | Deprecated in MongoDB 4.4. |
32-bit integer | 16 | “int” | |
Timestamp | 17 | “timestamp” | |
64-bit integer | 18 | “long” | |
Decimal128 | 19 | “decimal” | New in version 3.4. |
Min key | -1 | “minKey” | |
Max key | 127 | “maxKey” |
- 存在检查
查询不包含item字段的文档
$exists
db.inventory.find( { item : { $exists: false } } )
聚合管道更新
@since4.2
使用聚合管道可以实现更具表达力的更新语句
什么是管道?pipline ? ===> 就是 ==> [ ]
$addFields 新增字段 |
$set 更新字段 |
$project |
$unset |
$replaceRoot |
$replaceWith |
$set 更新字段
$trunc 将数字阶段为整数或指定的小数位
返回整数
db.samples.aggregate([
{ $project: { truncatedValue: { $trunc: [ "$value", 0 ] } } }
])
返回保留一位小数
db.samples.aggregate([
{ $project: { truncatedValue: { $trunc: [ "$value", 1 ] } } }
])
-1是什么意思?
The following aggregation returns value truncated to the first place
下面的聚合返回截断到第一个位置的值
{ _id: 1, value: 19.25 }
db.samples.aggregate([
{ $project: { truncatedValue: { $trunc: [ "$value", -1 ] } } }
])
{ "_id" : 1, "truncatedValue" : 10 }
$addFields 新增字段
$mergeObjects 有就更新,没有就填充
$concatArrays 数组拼接
$map 将表达式应用于数组中的每个项目,并返回具有应用结果的数组
db.collection.updateOne() |
即使多个文档可能与指定的过滤器匹配,也最多更新一个与指定的过滤器匹配的文档。3.2版中的新功能。 |
db.collection.updateMany() |
更新所有与指定过滤器匹配的文档。3.2版中的新功能。 |
db.collection.replaceOne() |
即使多个文档可能与指定过滤器匹配,也最多替换一个与指定过滤器匹配的文档。3.2版中的新功能。 |
db.collection.update() |
更新或替换与指定过滤器匹配的单个文档,或更新与指定过滤器匹配的所有文档。默认情况下,该db.collection.update() 方法更新单个文档。要更新多个文档,请使用multi选项。 |
db.collection.findOneAndReplace() |
|
db.collection.findOneAndUpdate() |
|
db.collection.findAndModify() |
|
db.collection.save() |
|
db.collection.bulkWrite() |
批量操作
try {
db.characters.bulkWrite(
[
{ insertOne :
{
"document" :
{
"_id" : 4, "char" : "Dithras", "class" : "barbarian", "lvl" : 4
}
}
},
{ insertOne :
{
"document" :
{
"_id" : 5, "char" : "Taeln", "class" : "fighter", "lvl" : 3
}
}
},
{ updateOne :
{
"filter" : { "char" : "Eldon" },
"update" : { $set : { "status" : "Critical Injury" } }
}
},
{ deleteOne :
{ "filter" : { "char" : "Brisbane" } }
},
{ replaceOne :
{
"filter" : { "char" : "Meldane" },
"replacement" : { "char" : "Tanys", "class" : "oracle", "lvl" : 4 }
}
}
]
);
}
catch (e) {
print(e);
}
聚合函数
$lookup
table joins 表关联
什么意思?
联合查询,将关联表的数据以as的字段进行绑定
db.orders.insert([
{ "_id" : 1, "item" : "almonds", "price" : 12, "quantity" : 2 },
{ "_id" : 2, "item" : "pecans", "price" : 20, "quantity" : 1 },
{ "_id" : 3 }
])
db.inventory.insert([
{ "_id" : 1, "sku" : "almonds", "description": "product 1", "instock" : 120 },
{ "_id" : 2, "sku" : "bread", "description": "product 2", "instock" : 80 },
{ "_id" : 3, "sku" : "cashews", "description": "product 3", "instock" : 60 },
{ "_id" : 4, "sku" : "pecans", "description": "product 4", "instock" : 70 },
{ "_id" : 5, "sku": null, "description": "Incomplete" },
{ "_id" : 6 }
])
db.orders.aggregate([ // 左表
{
$lookup:
{
from: "inventory", // 右表
localField: "item", // 左表关键字
foreignField: "sku", // 右表关键字
as: "inventory_docs" // 右表关联数据别名
}
}
])
{
"_id" : 1,
"item" : "almonds",
"price" : 12,
"quantity" : 2,
"inventory_docs" : [
{ "_id" : 1, "sku" : "almonds", "description" : "product 1", "instock" : 120 }
]
}
{
"_id" : 2,
"item" : "pecans",
"price" : 20,
"quantity" : 1,
"inventory_docs" : [
{ "_id" : 4, "sku" : "pecans", "description" : "product 4", "instock" : 70 }
]
}
{
"_id" : 3,
"inventory_docs" : [
{ "_id" : 5, "sku" : null, "description" : "Incomplete" },
{ "_id" : 6 }
]
}
$out
SELECT INTO NEW_TABLE
将聚合管道返回的文档,输出到指定的集合
就是将查询出来的结果插入到另外的集合中(可以是不同的数据库)
插入到同一个数据库中
- 查询test 数据库的 books 集合
- 将返回结果写入 authors 集合中
db.getSiblingDB("test").books.aggregate( [
{ $group : { _id : "$author", books: { $push: "$title" } } },
{ $out : "authors" }
] )
插入到不同的数据库中
- 查询test 数据库的 books 集合
- 将返回结果插入到 reporting 数据库的 authors 集合中
db.getSiblingDB("test").books.aggregate( [
{ $group : { _id : "$author", books: { $push: "$title" } } },
{ $out : { db: "reporting", coll: "authors" } }
] )
数据库操作相关常用方法介绍
https://blog.csdn.net/zhaoyong421127/article/details/51242691
$merge
简单的merge操作和out的效果是一样的,都是将上一步的结果插入到一个新的集合中,只能是当前数据库
db.sales.aggregate( [
{ $project: { _id: 0 } },
{ $merge : { into : "newCollection" } }
] )
on -指定条件
whenMatched : 当on的数据被匹配到(已存在)时,执行 ‘replace’ 更新操作
whenNotMatched :当on的数据没有被匹配到时(不存在),执行插入操作
db.getSiblingDB("zoo").salaries.aggregate( [
{ $group: { _id: { fiscal_year: "$fiscal_year", dept: "$dept" }, salaries: { $sum: "$salary" } } },
{ $merge : { into: { db: "reporting", coll: "budgets" }, on: "_id", whenMatched: "replace", whenNotMatched: "insert" } }
] )
当数据被匹配到的时候,增加新的字段 thumpbsup , thumbsdown]
没被匹配上进行插入
db.votes.aggregate([
{ $match: { date: { $gte: new Date("2019-05-07"), $lt: new Date("2019-05-08") } } },
{ $project: { _id: { $dateToString: { format: "%Y-%m", date: "$date" } }, thumbsup: 1, thumbsdown: 1 } },
{ $merge: {
into: "monthlytotals",
on: "_id",
whenMatched: [
{ $addFields: {
thumbsup: { $add:[ "$thumbsup", "$$new.thumbsup" ] },
thumbsdown: { $add: [ "$thumbsdown", "$$new.thumbsdown" ] }
} } ],
whenNotMatched: "insert"
} }
])
对日期格式进行转换
$dateToString: { format: "%Y-%m", date: "$date" }
如果输出集合具有文档:
{ _id: 1, a: 1, b: 1 }
并且聚合结果有文件:
{ _id: 1, b: 5, z: 1 }
然后,合并的文档为:
{ _id: 1, a: 1, b: 5, z: 1 }
$unionWith
联合查询
db.suppliers.aggregate([
{ $project: { state: 1, _id: 0 } },
{ $unionWith: { coll: "warehouses", pipeline: [ { $project: { state: 1, _id: 0 } } ]} }
])
$unwind
数据展开
db.inventory.insertOne({ "_id" : 1, "item" : "ABC1", sizes: [ "S", "M", "L"] })
数据展开
db.inventory.aggregate( [ { $unwind : "$sizes" } ] )
展开后的结果
{ "_id" : 1, "item" : "ABC1", "sizes" : "S" }
{ "_id" : 1, "item" : "ABC1", "sizes" : "M" }
{ "_id" : 1, "item" : "ABC1", "sizes" : "L" }
$unset
$unset是$project阶段的别名,用于删除/排除字段:
什么意思?
查询的时候,不显示某些字段
$facet
同一阶段。可以在一个文档上同时添加多个pipline,输出多个结果
返回的结果以文档数组形式存储
啥意思?
一个文档包含两个数字 1,2
可以同时计算 + - × ÷
返回结果 [3,-1,2,0.5]
文本搜索
文本索引,,支持对字符串内容的文本搜索查询
- 在文本集合上创建索引, 一个集合只能有一个文本搜索索引,该索引可涵盖多字段
创建索引
db.stores.createIndex( { name: "text", description: "text" } )
进行查询
多字符串查询查询, 分别包含 java ,coffee, shop 内容的数据
db.stores.find( { $text: { $search: "java coffee shop" } } )
单字符串查询
db.stores.find( { $text: { $search: ""coffee shop"" } } )
包含 java, shop 不包含 coffee
db.stores.find( { $text: { $search: "java shop -coffee" } } )
$accumulator (aggregation)
$addToSet (aggregation)
$allElementsTrue (aggregation)
$anyElementTrue (aggregation)
$binarySize (aggregation)
$bsonSize (aggregation)
$ceil (aggregation)
$cmp (aggregation)
$concat (aggregation)
$cond (aggregation)
$convert (aggregation)
$degreesToRadians (aggregation)
$filter (aggregation)
$first (aggregation accumulator)
$first (aggregation)
$floor (aggregation)
$function (aggregation)
$ifNull (aggregation)
$in (aggregation)
$last (aggregation accumulator)
$last (aggregation)
$let (aggregation)
$literal (aggregation)
$ln (aggregation)
$ltrim (aggregation)
$map (aggregation)
$mergeObjects (aggregation)
$meta$min (aggregation)
$not (aggregation)
$or (aggregation)
$push (aggregation)
$radiansToDegrees (aggregation)
$range (aggregation)
$reduce (aggregation)
$regexFind (aggregation)
$regexFindAll (aggregation)
$regexMatch (aggregation)
$replaceOne (aggregation)
$replaceAll (aggregation)
$reverseArray (aggregation)
$round (aggregation)
$rtrim (aggregation)
$second (aggregation)
$setDifference (aggregation)
$setEquals (aggregation)
$setIntersection (aggregation)
$setIsSubset (aggregation)
$setUnion (aggregation)
$size (aggregation)
$slice (aggregation)
$split (aggregation)
$stdDevPop (aggregation)
$stdDevSamp (aggregation)
$strcasecmp (aggregation)
$strLenBytes (aggregation)
$strLenCP (aggregation)
$substr (aggregation)
$substrBytes (aggregation)
$substrCP (aggregation)
$subtract (aggregation)
$switch (aggregation)
功能函数
$indexOfArray (aggregation)
$indexOfBytes (aggregation)
$indexOfCP (aggregation)
$isArray (aggregation)
$isNumber (aggregation)
数组处理
$arrayElemAt (aggregation)
$arrayToObject (aggregation)
$concatArrays (aggregation)
$objectToArray (aggregation)
字符串处理
数据类型处理
$toBool (aggregation)
$toDate (aggregation)
$toDecimal (aggregation)
$toDouble(aggregation)
$toInt (aggregation)
$toLong (aggregation)
$toObjectId (aggregation)
$toString (aggregation)
$trunc (aggregation)
字符串处理
$toLower (aggregation)
$toUpper (aggregation)
$trim (aggregation)
日期处理
$dateFromParts (aggregation)
$dateToParts (aggregation)
$dateFromString (aggregation)
$dateToString (aggregation)
$dayOfMonth (aggregation)
$dayOfWeek (aggregation)
$dayOfYear (aggregation)
$type (aggregation)
$week (aggregation)
$year (aggregation)
$hour (aggregation)
$month (aggregation)
$millisecond (aggregation)
$minute (aggregation)
$zip (aggregation)
$isoDayOfWeek (aggregation)
$isoWeek (aggregation)
$isoWeekYear (aggregation)
数学计算
$add (aggregation)
$divide (aggregation)
$abs (aggregation)
$multiply (aggregation)
$mod (aggregation)
$avg (aggregation)
$max (aggregation)
三角函数
$log (aggregation)
$log10 (aggregation)
$sin (aggregation)
$sqrt (aggregation)
$sum (aggregation)
$tan (aggregation)
$cos (aggregation)
$atanh (aggregation)
$atan2 (aggregation)
$asin (aggregation)
$asinh (aggregation)
$atan (aggregation)
$acos (aggregation)
$acosh (aggregation)
$exp (aggregation)
比较运算符
$lt (aggregation)
$lte (aggregation)
$ne (aggregation)
$pow (aggregation)
$gt (aggregation)
$gte (aggregation)
$eq (aggregation)
- $abs (aggregation)
- $accumulator (aggregation)
- $acos (aggregation)
- $acosh (aggregation)
- $add (aggregation)
- $addToSet (aggregation)
- $allElementsTrue (aggregation)
- $and (aggregation)
- $anyElementTrue (aggregation)
- $arrayElemAt (aggregation)
- $arrayToObject (aggregation)
- $asin (aggregation)
- $asinh (aggregation)
- $atan (aggregation)
- $atan2 (aggregation)
- $atanh (aggregation)
- $avg (aggregation)
- $binarySize (aggregation)
- $bsonSize (aggregation)
- $ceil (aggregation)
- $cmp (aggregation)
- $concat (aggregation)
- $concatArrays (aggregation)
- $cond (aggregation)
- $convert (aggregation)
- $cos (aggregation)
- $dateFromParts (aggregation)
- $dateToParts (aggregation)
- $dateFromString (aggregation)
- $dateToString (aggregation)
- $dayOfMonth (aggregation)
- $dayOfWeek (aggregation)
- $dayOfYear (aggregation)
- $degreesToRadians (aggregation)
- $divide (aggregation)
- $eq (aggregation)
- $exp (aggregation)
- $filter (aggregation)
- $first (aggregation accumulator)
- $first (aggregation)
- $floor (aggregation)
- $function (aggregation)
- $gt (aggregation)
- $gte (aggregation)
- $hour (aggregation)
- $ifNull (aggregation)
- $in (aggregation)
- $indexOfArray (aggregation)
- $indexOfBytes (aggregation)
- $indexOfCP (aggregation)
- $isArray (aggregation)
- $isNumber (aggregation)
- $isoDayOfWeek (aggregation)
- $isoWeek (aggregation)
- $isoWeekYear (aggregation)
- $last (aggregation accumulator)
- $last (aggregation)
- $let (aggregation)
- $literal (aggregation)
- $ln (aggregation)
- $log (aggregation)
- $log10 (aggregation)
- $lt (aggregation)
- $lte (aggregation)
- $ltrim (aggregation)
- $map (aggregation)
- $max (aggregation)
- $mergeObjects (aggregation)
- $meta
- $min (aggregation)
- $millisecond (aggregation)
- $minute (aggregation)
- $mod (aggregation)
- $month (aggregation)
- $multiply (aggregation)
- $ne (aggregation)
- $not (aggregation)
- $objectToArray (aggregation)
- $or (aggregation)
- $pow (aggregation)
- $push (aggregation)
- $radiansToDegrees (aggregation)
- $range (aggregation)
- $reduce (aggregation)
- $regexFind (aggregation)
- $regexFindAll (aggregation)
- $regexMatch (aggregation)
- $replaceOne (aggregation)
- $replaceAll (aggregation)
- $reverseArray (aggregation)
- $round (aggregation)
- $rtrim (aggregation)
- $second (aggregation)
- $setDifference (aggregation)
- $setEquals (aggregation)
- $setIntersection (aggregation)
- $setIsSubset (aggregation)
- $setUnion (aggregation)
- $size (aggregation)
- $sin (aggregation)
- $slice (aggregation)
- $split (aggregation)
- $sqrt (aggregation)
- $stdDevPop (aggregation)
- $stdDevSamp (aggregation)
- $strcasecmp (aggregation)
- $strLenBytes (aggregation)
- $strLenCP (aggregation)
- $substr (aggregation)
- $substrBytes (aggregation)
- $substrCP (aggregation)
- $subtract (aggregation)
- $sum (aggregation)
- $switch (aggregation)
- $tan (aggregation)
- $toBool (aggregation)
- $toDate (aggregation)
- $toDecimal (aggregation)
- $toDouble(aggregation)
- $toInt (aggregation)
- $toLong (aggregation)
- $toObjectId (aggregation)
- $toString (aggregation)
- $toLower (aggregation)
- $toUpper (aggregation)
- $trim (aggregation)
- $trunc (aggregation)
- $type (aggregation)
- $week (aggregation)
- $year (aggregation)
- $zip (aggregation)
- $ addFields(聚合)
- $ bucket(汇总)
- $ bucketAuto(聚合)
- $ collStats(汇总)
- $ count(汇总)
- $ currentOp(汇总)
- $ facet(汇总)
- $ geoNear(汇总)
- $ graphLookup(汇总)
- $ group(汇总)
- $ indexStats(汇总)
- $ limit(汇总)
- $ listLocalSessions
- $ listSessions
- $ lookup(汇总)
- $ match(汇总)
- $合并(汇总)
- $ out(汇总)
- $ planCacheStats
- $ project(汇总)
- $ redact(汇总)
- $ replaceRoot(聚合)
- $ replaceWith(汇总)
- $ sample(汇总)
- $ sampleRate(汇总)
- $ set(汇总)
- $ skip(汇总)
- $ sort(汇总)
- $ sortByCount(汇总)
- $ unionWith(聚合)
- $ unset(汇总)
- $ unwind(汇总)
$ addFields(聚合)
$ bucket(汇总)
$ bucketAuto(聚合)
$ collStats(汇总)
$ count(汇总)
$ currentOp(汇总)
$ facet(汇总)
$ geoNear(汇总)
$ graphLookup(汇总)
$ group(汇总)
$ indexStats(汇总)
$ limit(汇总)
$ listLocalSessions
$ listSessions
$ lookup(汇总)
$ match(汇总)
$合并(汇总)
$ out(汇总)
$ planCacheStats
$ project(汇总)
$ redact(汇总)
$ replaceRoot(聚合)
$ replaceWith(汇总)
$ sample(汇总)
$ sampleRate(汇总)
$ set(汇总)
$ skip(汇总)
$ sort(汇总)
$ sortByCount(汇总)
$ unionWith(聚合)
$ unset(汇总)
$ unwind(汇总)