我在 mongoDB 中有这个查询，它产生了我想要的结果。但现在我正尝试在 java 中使用它。

这是 MongoDB 中的查询:

var red = function(doc, out) {
out.count_order++;
out.sum_qty += doc.quantity;
out.sum_base_price += doc.extendedprice;
out.sum_disc_price += doc.extendedprice * (1 - doc.discount);
out.sum_charge += doc.extendedprice * (1 - doc.discount) * (1 + doc.tax);
out.avg_disc += doc.discount;
};

var avg = function(out) {
out.avg_qty = out.sum_qty / out.count_order;
out.avg_price = out.sum_base_price / out.count_order;
out.avg_disc = out.avg_disc / out.count_order;
};

db.lineitems.group( {
key : { returnflag : true, linestatus : true},
cond : { "shipdate" : {$lte: 19980801}},
initial: { count_order : 0, sum_qty : 0, sum_base_price : 0, sum_disc_price : 0,
sum_charge : 0, avg_disc : 0},
reduce : red,
finalize : avg
});

现在我在 Java 中使用它的方式，但我不知道如何使用 avg 函数。

    String avg = "var avg = function(out) {"
            + "out.avg_qty = out.sum_qty / out.count_order;"
            + "out.avg_price = out.sum_base_price / out.count_order;"
            + "out.avg_disc = out.avg_disc / out.count_order;};";

    String reduce = "function(doc, out) {"
            + "out.count_order++;"
            + "out.sum_qty += doc.quantity;"
            + "out.sum_base_price += doc.extendedprice;"
            + "out.sum_disc_price += doc.extendedprice * (1 - doc.discount);"
            + "out.sum_charge += doc.extendedprice * (1 - doc.discount) * (1 + doc.tax);"
            + "out.avg_disc += doc.discount;};";

    String finalize = "function(out) {"
            + "out.avg_qty = out.sum_qty / out.count_order;"
            + "out.avg_price = out.sum_base_price / out.count_order;"
            + "out.avg_disc = out.avg_disc / out.count_order;};";

    MapReduceIterable<Document> iterable = collection.mapReduce(**????**, reduce).finalizeFunction(finalize);

如何使用该功能？

最佳答案

为此使用聚合框架比调用 .group() 更好。方法，这当然是聚合框架实际存在之前的较旧实现。

在 shell 中应用的逻辑是:

db.lineitems.aggregate([
    { "$match": { "shipdate": { "$lte": 19980801 } },
    { "$group": {
        "_id": {
            "returnflag": "$returnflag",
            "linestatus": "$linestatus"
        },
        "count": { "$sum": 1 },
        "sum_qty": { "$sum": "$quantity" },
        "avg_qty": { "$avg": "$quantity" },
        "sum_base_price": { "$sum": "$extendedprice" },
        "avg_base_price": { "$avg": "$extendedprice" },
        "sum_disc_price": {
            "$sum": {
                "$multiply": [
                    "$extendedprice",
                    { "$subtract": [ 1, "$discount" ] }
                ]
            }
        },
        "avg_disc_price": {
            "$avg": {
                "$multiply": [
                    "$extendedprice",
                    { "$subtract": [ 1, "$discount" ] }
                ]
            }
        },
        "sum_charge": {
            "$sum": {
                "$multiply": [
                    "$extendedprice",
                    { "$subtract": [ 1, "$discount" ] },
                    { "$add": [ 1, "$tax" ] }
                ]
            }
        },
        "avg_disc": { "$avg": "$discount" }
    }}
])

作为一个非常高效的聚合框架$group管道阶段运算符，它在 native 编码操作中执行所有相同的操作。有 $sum和 $avg内置累加器以及其他数学运算。

简而言之，作为“原生编码”而不依赖于“JavaScript 解释”，执行速度比.group() 所能提供的要快得多。此外，它确实应该相当简单易懂。

将其翻译成 Java 会是这样的

List<Document> pipeline = Arrays.<Document>asList(
  new Document(
    "$match", new Document(
      "shipdate", new Document(
        "$lte", 19980801             
      )
    )
  ),
  new Document(
    "$group", new Document(
      "_id", new Document(
        "returnflag", "$returnflag"
      ).append( "linestatus", "$linestatus" )
    ).append(
      "count", new Document( "$sum", 1 )
    ).append(
      "sum_qty", new Document( "$sum", "$quantity" )
    ).append(
      "avg_qty", new Document( "$avg", "$quantity" )
    ).append(
      "sum_base_price", new Document( "$sum", "$extendedprice" )
    ).append(
      "avg_base_price", new Document( "$avg", "$extendedprice" )
    ).append(
      "sum_disc_price", new Document(
        "$sum", new Document(
          "$multiply", Arrays.asList(
            "$extendedprice",
            new Document(
              "$subtract", Arrays.asList(1, "$discount")
            )
          )
        )
      )
    ).append(
      "avg_disc_price", new Document(
        "$avg", new Document(
          "$multiply", Arrays.asList(
            "$extendedprice",
            new Document(
              "$subtract", Arrays.asList(1, "$discount")
            )
          )
        )
      )
    ).append(
      "sum_charge", new Document(
        "$sum", new Document(
          "$multiply", Arrays.asList(
            "$extendedprice",
            new Document(
              "$subtract", Arrays.asList(1, "$discount")
            ),
            new Document(
              "$add", Arrays.asList(1, "$tax")
            )
          )
        )
      )
    ).append(
      "avg_disc", new Document( "$avg", "$discount" )
    )
  )
);

AggregateIterable<Document> result = collection.aggregate(pipeline);

关于java - 如何使用 Java 运行 .group()，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/36327820/