Analyze Query Performance分析查询性能

The following query retrieves documents where the quantity field has a value between 100 and 200, inclusive:以下查询检索quantity字段值介于100和200之间（包括100和200）的文档：

db.inventory.find( { quantity: { $gte: 100, $lte: 200 } } )

The query returns the following documents:查询返回以下文档：

{ "_id" : 2, "item" : "f2", "type" : "food", "quantity" : 100 }
{ "_id" : 3, "item" : "p1", "type" : "paper", "quantity" : 200 }
{ "_id" : 4, "item" : "p2", "type" : "paper", "quantity" : 150 }

To view the query plan selected, chain the cursor.explain("executionStats") cursor method to the end of the find command:要查看所选的查询计划，请将cursor.explain("executionStats")游标方法链接到find命令的末尾：

db.inventory.find(
   { quantity: { $gte: 100, $lte: 200 } }
).explain("executionStats")

explain() returns the following results:返回以下结果：

{
   queryPlanner: {
         ...
         winningPlan: {
            queryPlan: {
               stage: 'COLLSCAN',
               ...
            }
         }
   },
   executionStats: {
      executionSuccess: true,
      nReturned: 3,
      executionTimeMillis: 0,
      totalKeysExamined: 0,
      totalDocsExamined: 10,
      executionStages: {
         stage: 'COLLSCAN',
         ...
      },
      ...
   },
   ...
}

• queryPlanner.winningPlan.queryPlan.stage displays COLLSCAN to indicate a collection scan.显示COLLSCAN以指示集合扫描。

  Collection scans indicate that the mongod had to scan the entire collection document by document to identify the results. 集合扫描表明mongod必须逐个文档扫描整个集合文档才能识别结果。This is a generally expensive operation and can result in slow queries.这通常是一个昂贵的操作，并且可能导致查询速度缓慢。

• executionStats.nReturned displays 3 to indicate that the query matches and returns three documents.显示3表示查询匹配并返回三个文档。

• executionStats.totalKeysExamined displays 0 to indicate that this is query is not using an index.显示0表示此查询未使用索引。

• executionStats.totalDocsExamined displays 10 to indicate that MongoDB had to scan ten documents (i.e. all documents in the collection) to find the three matching documents.显示10表示MongoDB必须扫描十个文档（即集合中的所有文档）才能找到三个匹配的文档。

The following query retrieves documents where the quantity field has a value between 100 and 200, inclusive:以下查询检索quantity字段值介于100和200之间（包括100和200）的文档：

Copy the following filter into the Compass query bar and click Find:将以下筛选器复制到Compass查询栏中，然后单击“查找”：

{ quantity: { $gte: 100, $lte: 200 } }

The query returns the following documents:查询返回以下文档：

To view the query plan selected:查看所选查询计划：

1. Click the Explain Plan tab for the test.inventory collection.单击test.inventory集合的“解释计划”选项卡。

2. Click Explain.单击“解释”。

MongoDB Compass displays the query plan as follows:MongoDB Compass显示查询计划如下：

Visual Tree可视化树

• The Query Performance Summary shows the execution stats of the query:“查询性能摘要”显示查询的执行统计信息：

  • Documents Returned displays 3 to indicate that the query matches and returns three documents.“返回的文档”显示3，表示查询匹配并返回三个文档。

  • Index Keys Examined displays 0 to indicate that this query is not using an index.“已检查的索引键”显示0，表示此查询未使用索引。

  • Documents Examined displays 10 to indicate that MongoDB had to scan ten documents (i.e. all documents in the collection) to find the three matching documents.“已检查的文档”显示10，表示MongoDB必须扫描10个文档（即集合中的所有文档）才能找到三个匹配的文档。

• Below the Query Performance Summary, MongoDB Compass displays the COLLSCAN query stage to indicate that a collection scan was used for this query.在“查询性能摘要”下面，MongoDB Compass显示COLLSCAN查询阶段，以指示此查询使用了集合扫描。

  Collection scans indicate that the mongod had to scan the entire collection document by document to identify the results. This is a generally expensive operation and can result in slow queries.集合扫描表明mongod必须逐个文档扫描整个集合文档才能识别结果。这通常是一个昂贵的操作，并且可能导致查询速度缓慢。

Raw JSON

The explain details can also be viewed in raw JSON format by clicking Raw JSON below the query bar:还可以通过单击查询栏下方的“Raw JSON”以原始JSON格式查看解释详细信息：

db.inventory.createIndex( { quantity: 1 } )

To view the query plan statistics, use the explain() method:要查看查询计划统计信息，请使用explain()方法：

db.inventory.find(
   { quantity: { $gte: 100, $lte: 200 } }
).explain("executionStats")

The explain() method returns the following results:explain()方法返回以下结果：

{
   queryPlanner: {
         ...
         winningPlan: {
            queryPlan: {
               stage: 'FETCH',
               inputStage: {
                  stage: 'IXSCAN',
                  keyPattern: {
                     quantity: 1
                  },
                  ...
               }
            }
         },
         rejectedPlans: [ ]
   },
   executionStats: {
         executionSuccess: true,
         nReturned: 3,
         executionTimeMillis: 0,
         totalKeysExamined: 3,
         totalDocsExamined: 3,
         executionStages: {
            ...
         },
         ...
   },
   ...
}

• queryPlanner.winningPlan.queryPlan.inputStage.stage displays IXSCAN to indicate index use.显示IXSCAN以指示索引的使用。

• executionStats.nReturned displays 3 to indicate that the query matches and returns three documents.显示3表示查询匹配并返回三个文档。

• executionStats.totalKeysExamined displays 3 to indicate that MongoDB scanned three index entries. 显示3表示MongoDB扫描了三个索引条目。The number of keys examined match the number of documents returned, meaning that the mongod only had to examine index keys to return the results. 检查的键数与返回的文档数相匹配，这意味着mongod只需检查索引键即可返回结果。The mongod did not have to scan all of the documents, and only the three matching documents had to be pulled into memory. mongod不必扫描所有文档，只需将三个匹配的文档提取到内存中。This results in a very efficient query.这将产生一个非常高效的查询。

• executionStats.totalDocsExamined display 3 to indicate that MongoDB scanned three documents.显示3表示MongoDB扫描了三个文档。

1. Click the Indexes tab for the test.inventory collection.单击test.inventory集合的“索引”选项卡。

2. Click Create Index.单击“创建索引”。

3. Select quantity from the Select a field name dropdown.从“选择字段名称”下拉列表中选择quantity。

4. Select 1 (asc) from the type dropdown.从类型下拉列表中选择1 (asc)。

5. Click Create.单击“创建”。

You can now see your newly created index in the Indexes tab:现在，您可以在“索引”选项卡中查看新创建的索引：

Return to the Explain Plan tab for the inventory collection and re-run the query from the previous step:返回inventory集合的“解释计划”选项卡，然后重新运行上一步骤中的查询：

{ quantity: { $gte: 100, $lte: 200 } }

MongoDB Compass displays the query plan as follows:MongoDB Compass显示查询计划如下：

Visual Tree可视化树

• The Query Performance Summary shows the execution stats of the query:“查询性能摘要”显示查询的执行统计信息：

  • Documents Returned displays 3 to indicate that the query matches and returns three documents.“返回的文档”显示3，表示查询匹配并返回三个文档。

  • Index Keys Examined displays 3 to indicate that MongoDB scanned three index entries. “已检查的索引键”显示3，表示MongoDB扫描了三个索引条目。The number of keys examined match the number of documents returned, meaning that the mongod only had to examine index keys to return the results. 检查的键数与返回的文档数相匹配，这意味着mongod只需检查索引键即可返回结果。The mongod did not have to scan all of the documents, and only the three matching documents had to be pulled into memory. mongod不必扫描所有文档，只需将三个匹配的文档提取到内存中。This results in a very efficient query.这将产生一个非常高效的查询。

  • Documents Examined displays 3 to indicate that MongoDB scanned three documents.“已检查的文档”显示3，表示MongoDB扫描了三个文档。

  • On the right-hand side of the Query Performance Summary, MongoDB Compass shows that the query used the quantity index.在“查询性能摘要”的右侧，MongoDB Compass显示查询使用了quantity索引。

• Below the Query Performance Summary, MongoDB Compass displays the query stages FETCH and IXSCAN. 在“查询性能摘要”下面，MongoDB Compass显示查询阶段FETCH和IXSCAN。IXSCAN indicates that the mongod used an index to satisfy the query before executing the FETCH stage and retrieving the documents.IXSCAN表示mongod在执行FETCH阶段和检索文档之前使用了一个索引来满足查询。

Raw JSON

The explain details can also be viewed in raw JSON format by clicking Raw JSON below the query bar:还可以通过单击查询栏下方的“Raw JSON”以原始JSON格式查看解释详细信息：