MongoDB index analysis explain

Today, Xiaobian uses the explain() method to analyze the use effect of indexes in the collection

1. Insert 100w records circularly first

for (var i = 0; i < 1000000; i++ ) { 
    db.person.insert({"name":"test"+i, "cardNo":i}) 
}

2. Check the insertion effect

> db.person.find()
{ "_id" : ObjectId("5c7c9e15a795b984b42ad96b"), "name" : "test0", "cardNo" : 0 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad96c"), "name" : "test1", "cardNo" : 1 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad96d"), "name" : "test2", "cardNo" : 2 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad96e"), "name" : "test3", "cardNo" : 3 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad96f"), "name" : "test4", "cardNo" : 4 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad970"), "name" : "test5", "cardNo" : 5 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad971"), "name" : "test6", "cardNo" : 6 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad972"), "name" : "test7", "cardNo" : 7 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad973"), "name" : "test8", "cardNo" : 8 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad974"), "name" : "test9", "cardNo" : 9 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad975"), "name" : "test10", "cardNo" : 10 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad976"), "name" : "test11", "cardNo" : 11 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad977"), "name" : "test12", "cardNo" : 12 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad978"), "name" : "test13", "cardNo" : 13 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad979"), "name" : "test14", "cardNo" : 14 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad97a"), "name" : "test15", "cardNo" : 15 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad97b"), "name" : "test16", "cardNo" : 16 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad97c"), "name" : "test17", "cardNo" : 17 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad97d"), "name" : "test18", "cardNo" : 18 }
{ "_id" : ObjectId("5c7c9e15a795b984b42ad97e"), "name" : "test19", "cardNo" : 19 }
Type "it" for more

3. Query analysis without index

> db.person.find({"name":"test890000"}).explain("executionStats")
{
    "queryPlanner" : {
        "plannerVersion" : 1,
        "namespace" : "test.person",
        "indexFilterSet" : false,
        "parsedQuery" : {
            "name" : {
                "$eq" : "test890000"
            }
        },
        "winningPlan" : {
            "stage" : "COLLSCAN",
            "filter" : {
                "name" : {
                    "$eq" : "test890000"
                }
            },
            "direction" : "forward"
        },
        "rejectedPlans" : [ ]
    },
    "executionStats" : {
        "executionSuccess" : true,
        "nReturned" : 1,
        "executionTimeMillis" : 389,
        "totalKeysExamined" : 0,
        "totalDocsExamined" : 1000000,
        "executionStages" : {
            "stage" : "COLLSCAN",
            "filter" : {
                "name" : {
                    "$eq" : "test890000"
                }
            },
            "nReturned" : 1,
            "executionTimeMillisEstimate" : 232,
            "works" : 1000002,
            "advanced" : 1,
            "needTime" : 1000000,
            "needYield" : 0,
            "saveState" : 7814,
            "restoreState" : 7814,
            "isEOF" : 1,
            "invalidates" : 0,
            "direction" : "forward",
            "docsExamined" : 1000000
        }
    },
    "serverInfo" : {
        "host" : "shengyulongdeMacBook-Pro-2.local",
        "port" : 27017,
        "version" : "4.0.3",
        "gitVersion" : "7ea530946fa7880364d88c8d8b6026bbc9ffa48c"
    },
    "ok" : 1
}

4. Create an ascending index for the name field

> db.person.createIndex({"name":1})
{
    "createdCollectionAutomatically" : false,
    "numIndexesBefore" : 1,
    "numIndexesAfter" : 2,
    "ok" : 1
}

5.explain view index analysis

> db.person.find({"name":"test890000"}).explain("executionStats")
{
    "queryPlanner" : {
        "plannerVersion" : 1,
        "namespace" : "test.person",
        "indexFilterSet" : false,
        "parsedQuery" : {
            "name" : {
                "$eq" : "test890000"
            }
        },
        "winningPlan" : {
            "stage" : "FETCH",
            "inputStage" : {
                "stage" : "IXSCAN",
                "keyPattern" : {
                    "name" : 1
                },
                "indexName" : "name_1",
                "isMultiKey" : false,
                "multiKeyPaths" : {
                    "name" : [ ]
                },
                "isUnique" : false,
                "isSparse" : false,
                "isPartial" : false,
                "indexVersion" : 2,
                "direction" : "forward",
                "indexBounds" : {
                    "name" : [
                        "[\"test890000\", \"test890000\"]"
                    ]
                }
            }
        },
        "rejectedPlans" : [ ]
    },
    "executionStats" : {
        "executionSuccess" : true,
        "nReturned" : 1,
        "executionTimeMillis" : 1,
        "totalKeysExamined" : 1,
        "totalDocsExamined" : 1,
        "executionStages" : {
            "stage" : "FETCH",
            "nReturned" : 1,
            "executionTimeMillisEstimate" : 0,
            "works" : 2,
            "advanced" : 1,
            "needTime" : 0,
            "needYield" : 0,
            "saveState" : 0,
            "restoreState" : 0,
            "isEOF" : 1,
            "invalidates" : 0,
            "docsExamined" : 1,
            "alreadyHasObj" : 0,
            "inputStage" : {
                "stage" : "IXSCAN",
                "nReturned" : 1,
                "executionTimeMillisEstimate" : 0,
                "works" : 2,
                "advanced" : 1,
                "needTime" : 0,
                "needYield" : 0,
                "saveState" : 0,
                "restoreState" : 0,
                "isEOF" : 1,
                "invalidates" : 0,
                "keyPattern" : {
                    "name" : 1
                },
                "indexName" : "name_1",
                "isMultiKey" : false,
                "multiKeyPaths" : {
                    "name" : [ ]
                },
                "isUnique" : false,
                "isSparse" : false,
                "isPartial" : false,
                "indexVersion" : 2,
                "direction" : "forward",
                "indexBounds" : {
                    "name" : [
                        "[\"test890000\", \"test890000\"]"
                    ]
                },
                "keysExamined" : 1,
                "seeks" : 1,
                "dupsTested" : 0,
                "dupsDropped" : 0,
                "seenInvalidated" : 0
            }
        }
    },
    "serverInfo" : {
        "host" : "shengyulongdeMacBook-Pro-2.local",
        "port" : 27017,
        "version" : "4.0.3",
        "gitVersion" : "7ea530946fa7880364d88c8d8b6026bbc9ffa48c"
    },
    "ok" : 1
}
  • executionStats.nReturned: number of documents returned
  • executionStats.executionTimeMillis: execution time, unit (ms)
  • executionStats.totalKeysExamined: index scan entry.
  • executionStats.totalDocsExamined: document scan entry

comparative analysis

Use index Do not use index
Search time 1ms 389ms
Index scan entry 1 0
Document scan entry 1 1000000

There is a big difference between using index and not using index!!!

Posted by ryeman98 on Tue, 26 Nov 2019 06:31:15 -0800