MongoDB中哪几种情况下的索引选择策略-数据库

这篇文章主要给大家介绍了关于MongoDB中哪几种情况下的索引选择策略的相关资料,文中通过图文以及实例代码介绍的非常详细，对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下

一、MongoDB如何选择索引

如果我们在Collection建了5个index，那么当我们查询的时候，MongoDB会根据查询语句的筛选条件、sort排序等来定位可以使用的index作为候选索引；然后MongoDB会创建对应数量的查询计划，并分别使用不同线程执行查询计划，最终会选择一个执行最快的index；但是这个选择也不是一成不变的，后续还会有一段时间根据实际执行情况动态调整；

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二、数据准备

for(let i = 0;i<1000000;i++){
    db.users.insertOne({
        "id":i,
        "name":'user'+i,
        "age":Math.floor(Math.random()*120),
        "created":new Date(ISODate().getTime() - 1000 * 60*i)
    });
}

三、正则对index的使用

MongoDB支持正则查询，在特定的情况其也是可以利用index获得查询性能的提升；

虽然MongDB执行正则会最大限度的使用index，但是不同的用法还是会影响对index的利用程度的；

执行以下普通正则表达式

从queryPlanner.winningPlan部分的COLLSCAN，可以看到正则表达式默认会进行全表的扫描；

从executionStats.executionStages部分可以看到COLLSCAN共扫描了1000000个文档，并返回1111个文档，总耗时794ms；

db.users.find({
    name:/user999/
    }).explain('executionStats')
    
{
    "queryPlanner" : {
        "plannerVersion" : 1,
        "namespace" : "test.users",
        "indexFilterSet" : false,        
        "winningPlan" : {
            "stage" : "COLLSCAN",
            "filter" : {
                "name" : {
                    "$regex" : "user999"
                }
            },
            "direction" : "forward"
        },
        "rejectedPlans" : [ ]
    },
    "executionStats" : {
        "executionSuccess" : true,
        "nReturned" : 1111,
        "executionTimeMillis" : 909,
        "totalKeysExamined" : 0,
        "totalDocsExamined" : 1000000,
        "executionStages" : {
            "stage" : "COLLSCAN",
            "filter" : {
                "name" : {
                    "$regex" : "user999"
                }
            },
            "nReturned" : 1111,
            "executionTimeMillisEstimate" : 794,
            "works" : 1000002,
            "advanced" : 1111,
            "needTime" : 998890,
            "needYield" : 0,
            "saveState" : 7830,
            "restoreState" : 7830,
            "isEOF" : 1,
            "invalidates" : 0,
            "direction" : "forward",
            "docsExamined" : 1000000
        }
    }
}

创建一个包含name的index；

db.users.createIndex({name:1})

再次执行上边的查询，可以看到使用了我们新建的name_1索引；但是从执行状态来看，还是扫描了全体的索引的key，并不能很好的利用index；

{
    "queryPlanner" : {
        "plannerVersion" : 1,
        "namespace" : "test.users",
        "indexFilterSet" : false,
        "parsedQuery" : {
            "name" : {
                "$regex" : "user999"
            }
        },
        "winningPlan" : {
            "stage" : "FETCH",
            "inputStage" : {
                "stage" : "IXSCAN",
                "filter" : {
                    "name" : {
                        "$regex" : "user999"
                    }
                },
                "keyPattern" : {
                    "name" : 1
                },
                "indexName" : "name_1"                
            }
        },
        "rejectedPlans" : [ ]
    },
    "executionStats" : {
        "executionSuccess" : true,
        "nReturned" : 1111,
        "executionTimeMillis" : 971,
        "totalKeysExamined" : 1000000,
        "totalDocsExamined" : 1111,
        "executionStages" : {
            "stage" : "FETCH",
            "nReturned" : 1111,
            "executionTimeMillisEstimate" : 887,            
            "docsExamined" : 1111,
            "alreadyHasObj" : 0,
            "inputStage" : {
                "stage" : "IXSCAN",
                "filter" : {
                    "name" : {
                        "$regex" : "user999"
                    }
                },
                "nReturned" : 1111,
                "executionTimeMillisEstimate" : 876,              
                "keyPattern" : {
                    "name" : 1
                },
                "indexName" : "name_1",              
                "keysExamined" : 1000000
            }
        }
    }
}

使用前缀匹配的话可以最大限度的利用index，从执行状态可以看到只检测了1111个index key；

db.users.find({
    name:/^user999/
    }).explain('executionStats')
    
{
    "queryPlanner" : {
        "plannerVersion" : 1,
        "namespace" : "test.users",
        "indexFilterSet" : false,
        "parsedQuery" : {
            "name" : {
                "$regex" : "^user999"
            }
        },
        "winningPlan" : {
            "stage" : "FETCH",
            "inputStage" : {
                "stage" : "IXSCAN",
                "keyPattern" : {
                    "name" : 1
                },
                "indexName" : "name_1"                
            }
        },
        "rejectedPlans" : [ ]
    },
    "executionStats" : {
        "executionSuccess" : true,
        "nReturned" : 1111,
        "executionTimeMillis" : 2,
        "totalKeysExamined" : 1111,
        "totalDocsExamined" : 1111,
        "executionStages" : {
            "stage" : "FETCH",
            "nReturned" : 1111,
            "executionTimeMillisEstimate" : 0
            "docsExamined" : 1111            
            "inputStage" : {
                "stage" : "IXSCAN",
                "nReturned" : 1111,
                "executionTimeMillisEstimate" : 0,
                "indexName" : "name_1",
                "keysExamined" : 1111
            }
        }
    }
}

即使是前缀匹配，如果忽略大小写的话也无法充分利用index了；

db.users.find({
    name:/^user999/i
    }).explain('executionStats')
    
{
    "queryPlanner" : {
        "plannerVersion" : 1,
        "namespace" : "test.users",
        "indexFilterSet" : false,
        "parsedQuery" : {
            "name" : {
                "$regex" : "user999",
                "$options" : "i"
            }
        },
        "winningPlan" : {
            "stage" : "FETCH",
            "inputStage" : {
                "stage" : "IXSCAN",
                "filter" : {
                    "name" : {
                        "$regex" : "user999",
                        "$options" : "i"
                    }
                },
                "keyPattern" : {
                    "name" : 1
                },
                "indexName" : "name_1"
            }
        },
        "rejectedPlans" : [ ]
    },
    "executionStats" : {
        "executionSuccess" : true,
        "nReturned" : 1111,
        "executionTimeMillis" : 943,
        "totalKeysExamined" : 1000000,
        "totalDocsExamined" : 1111,
        "executionStages" : {
            "stage" : "FETCH",
            "nReturned" : 1111,
            "executionTimeMillisEstimate" : 833,
            "works" : 1000001,
            "inputStage" : {
                "stage" : "IXSCAN",
                "filter" : {
                    "name" : {
                        "$regex" : "user999",
                        "$options" : "i"
                    }
                },
                "nReturned" : 1111,
                "executionTimeMillisEstimate" : 833,
                "keyPattern" : {
                    "name" : 1
                },
                "indexName" : "name_1"
                "keysExamined" : 1000000
            }
        }
    }
}

四、$or从句对索引的利用

MongoDB执行$or从句的时候，会将所有的从句作为逻辑的整体，要不就都使用index，要不就都进行全表扫描；

执行以下的查询语句；

db.users.find({
    $or:[
        {name:/^user666

目录

一、MongoDB如何选择索引

二、数据准备

三、正则对index的使用

四、$or从句对索引的利用