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  • mongodb 语句和SQL语句对应(SQL to Aggregation Mapping Chart)

    SQL to Aggregation Mapping Chart

    https://docs.mongodb.com/manual/reference/sql-aggregation-comparison/

    The aggregation pipeline allows MongoDB to provide native aggregation capabilities that corresponds to many common data aggregation operations in SQL.

    The following table provides an overview of common SQL aggregation terms, functions, and concepts and the corresponding MongoDB aggregation operators:

    SQL Terms, Functions, and ConceptsMongoDB 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 aggregation statements and the corresponding MongoDB statements. The examples in the table assume the following conditions:

    • The SQL examples assume two tables, orders and order_lineitem that join by theorder_lineitem.order_id and the orders.id columns.

    • The MongoDB examples assume one collection orders that contain documents 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 ExampleMongoDB ExampleDescription
    SELECT COUNT(*) AS count
    FROM orders
    
    db.orders.aggregate( [
       {
         $group: {
            _id: null,
            count: { $sum: 1 }
         }
       }
    ] )
    
    Count all records from orders
    SELECT SUM(price) AS total
    FROM orders
    
    db.orders.aggregate( [
       {
         $group: {
            _id: null,
            total: { $sum: "$price" }
         }
       }
    ] )
    
    Sum the price field from orders
    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 unique cust_idord_dategrouping, sum the price 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 the cust_id and the 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_idord_dategrouping, sum the price field and return only where the sum 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_id with status A, 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_id with status A, sum the price field and return only where the sum 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 corresponding line item qty fields 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: {
                   month: { $month: "$ord_date" },
                   day: { $dayOfMonth: "$ord_date" },
                   year: { $year: "$ord_date"}
               }
            }
         }
       },
       {
         $group: {
            _id: null,
            count: { $sum: 1 }
         }
       }
    ] )
    
    Count the number of distinctcust_idord_date groupings. Excludes the time portion of the d
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  • 原文地址:https://www.cnblogs.com/sha0830/p/5630810.html
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