Mongodb 3.2 SQL对应聚合 官方

SQL to Aggregation Mapping Chart¶

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The aggregation pipeline allowsMongoDB to provide native aggregation capabilities that corresponds tomany common data aggregation operations in SQL.

The following table provides an overview of common SQL aggregationterms, functions, and concepts and the corresponding MongoDBaggregation operators:

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
join	$lookup New in version 3.2.

Examples

The following table presents a quick reference of SQL aggregationstatements and the corresponding MongoDB statements. The examples inthe table assume the following conditions:

• The SQL examples assume two tables, orders andorder_lineitem that join by theorder_lineitem.order_id andtheorders.id columns.

• The MongoDB examples assume one collection orders that containdocuments of the following prototype:

  {
    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 } ]
  }
  

SQL Example	MongoDB Example	Description
SELECT COUNT(*) AS count FROM orders	db.orders.aggregate( [ { $group: { _id: null, count: { $sum: 1 } } } ] )	Count all recordsfrom orders
SELECT SUM(price) AS total FROM orders	db.orders.aggregate( [ { $group: { _id: null, total: { $sum: "$price" } } } ] )	Sum the price fieldfromorders
SELECT cust_id, SUM(price) AS total FROM orders GROUP BY cust_id	db.orders.aggregate( [ { $group: { _id: "$cust_id", total: { $sum: "$price" } } } ] )	For each unique cust_id,sum theprice field.
SELECT cust_id, SUM(price) AS total FROM orders GROUP BY cust_id ORDER BY total	db.orders.aggregate( [ { $group: { _id: "$cust_id", total: { $sum: "$price" } } }, { $sort: { total: 1 } } ] )	For each unique cust_id,sum theprice field,results sorted by sum.
SELECT cust_id, ord_date, SUM(price) AS total FROM orders GROUP BY cust_id, ord_date	db.orders.aggregate( [ { $group: { _id: { cust_id: "$cust_id", ord_date: { month: { $month: "$ord_date" }, day: { $dayOfMonth: "$ord_date" }, year: { $year: "$ord_date"} } }, total: { $sum: "$price" } } } ] )	For each uniquecust_id,ord_date grouping,sum theprice field.Excludes the time portion of the date.
SELECT cust_id, count(*) FROM orders GROUP BY cust_id HAVING count(*) > 1	db.orders.aggregate( [ { $group: { _id: "$cust_id", count: { $sum: 1 } } }, { $match: { count: { $gt: 1 } } } ] )	For cust_id with multiple records,return thecust_id andthe corresponding record count.
SELECT cust_id, ord_date, SUM(price) AS total FROM orders GROUP BY cust_id, ord_date HAVING total > 250	db.orders.aggregate( [ { $group: { _id: { cust_id: "$cust_id", ord_date: { month: { $month: "$ord_date" }, day: { $dayOfMonth: "$ord_date" }, year: { $year: "$ord_date"} } }, total: { $sum: "$price" } } }, { $match: { total: { $gt: 250 } } } ] )	For each unique cust_id,ord_dategrouping, sum theprice fieldand return only where thesum is greater than 250.Excludes the time portion of the date.
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" } } } ] )	For each unique cust_idwith statusA,sum the price field.
SELECT cust_id, SUM(price) as total FROM orders WHERE status = 'A' GROUP BY cust_id HAVING total > 250	db.orders.aggregate( [ { $match: { status: 'A' } }, { $group: { _id: "$cust_id", total: { $sum: "$price" } } }, { $match: { total: { $gt: 250 } } } ] )	For each unique cust_idwith statusA,sum the price field and returnonly where thesum is greater than 250.
SELECT cust_id, SUM(li.qty) as qty FROM orders o, order_lineitem li WHERE li.order_id = o.id GROUP BY cust_id	db.orders.aggregate( [ { $unwind: "$items" }, { $group: { _id: "$cust_id", qty: { $sum: "$items.qty" } } } ] )	For each unique cust_id,sum the correspondingline itemqty fieldsassociated with theorders.
SELECT COUNT(*) FROM (SELECT cust_id, ord_date FROM orders GROUP BY cust_id, ord_date) as DerivedTable	db.orders.aggregate( [ { $group: { _id: { cust_id: "$cust_id", ord_date: { month: { $month: "$ord_date" }, day: { $dayOfMonth: "$ord_date" }, year: { $year: "$ord_date"} } } } }, { $group: { _id: null, count: { $sum: 1 } } } ] )	Count the number of distinctcust_id,ord_date groupings.Excludes the time portion of the date.

Additional Resources

• MongoDB and MySQL Compared
• Quick Reference Cards
• MongoDB Database Modernization Consulting Package

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