Map of MongoDB and SQL aggregation operations

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	No direct corresponding operator; however, the $unwindoperator allows for somewhat similar functionality, but with fields embedded within the Docum Ent.

Instance:
[TD]

SQL Example	MongoDB Example	Description
SELECT COUNT (*)  as Count from Orders	Db.orders.aggregate ([{$group: {_id:null, Count: {$sum: 1}}])	Count All Records Fromorders
SELECT SUM (Price) as Total from Orders	Db.orders.aggregate ([{$group: {_id:null, total: {$sum: "$price"}}])	Sum theprice field from orders, this is very useful, see the official note, said _id is necessary, but did not think can be null,
SELECT  cust_id,        SUM (price)   as total from  orders GROUP   by  cust_id	db.orders.aggregate ([   {$group: {_id: "$cust _id",               total: {$sum: "$price"}}]	for each uniquecust_id, sum the Pricefield.
SELECT  cust_id,        SUM (price)   as total from  orders GROUP   by cust_id ORDER  , by  total	db.orders.aggregate ([   {$group: {_id: "$cust _id",                total: {$sum: "$price"}}},   {$sort: {total:1}}])	for each uniquecust_id, sum of the Pricefield, results sorted by sum.
SELECT  cust_id,       ord_date,      &NBSP SUM (Price)  , as  total from  orders GROUP by  cust_id, ord_date	db.orders.aggregate ([   {$group: {_id: {cust_id: "$cust _id",                   ;    ord_date: "$ord _date"},               total: {$sum: "$p Rice "}}])	for each uniquecust_id,ord_dategrouping, sum the Pricefield.
SELECT  cust_id,  Count (*) from orders GROUP   by  cust_id have   Count (*) > 1	db.orders.aggregate ([   {$group: {_id: "$cust _id", & nbsp              count: {$sum: 1}}},   {$match: {count: {$gt: 1 }}])	for cust_idwith multiple records, return thecust_id and the corresponding R Ecord count.
SELECT  cust_id,       ord_date,      &NBSP SUM (Price)  , as  total from  orders GROUP by  cust_id, ord_date have  total > 250	db.orders.aggregate ([   {$group: {_id: {cust_id: "$cust _id",     & nbsp;                ord_date: "$ord _date"},               total: {$sum: "$price"}}},   {$match: {total: {$gt: 250}} }])	for each uniquecust_id,ord_dategrouping, sum the Pricefield and return only whe Re the sum is greater than.
SELECT  cust_id,        SUM (price)   as total from  orders WHERE   status = ' A ' GROUP   by  cust_id	db.orders.aggregate ([   {$match: {status: ' A '}},   {$group: {_id: "$cust _id", &N Bsp              total: {$sum: "$price"}}])	for each uniquecust_id with status A, sum the Pricefield.
SELECT  cust_id,        SUM (price)   as total from  orders WHERE   status = ' A ' GROUP   by  cust_id have  total  > 250	db.orders.aggregate ([   {$match: {status: ' A '}} ,   {$group: {_id: "$cust _id",               total: {$sum: "$price"}}},   {$match: {total: {$gt: +}}])	for each UNIQUECU st_id with status A, sum the Pricefield and return only where the sum is greater than.
SELECT  cust_id,        SUM (Li.qty)   as qty from  orders o,     order_ LineItem li WHERE  li.order_id = o.id GROUP   by cust_id	db.orders.aggregate ([   {$unwind: "$items"},    {$group: {_id: "$cust _id",               qty: {$sum: "$i Tems.qty "}}])	for each uniquecust_id, sum of the corresponding line item Qtyfields associated with the orders.
SELECT   COUNT (*) from   ( SELECT  cust_id, ord_date       from  orders       GROUP   by cust_id, ord_date)   as  derivedtable	db.orders.aggregate ([   {$group: {_id: {cust_id: "$cust _id",                      ord_date: "$ord _ Date "}}},   {$group: {_id:null, Count: {$sum: 1}}])