解释MongoDB Vector Search 结果

1
{
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  explainVersion: '1',
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  stages: [
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    {
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      '$vectorSearch': {
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        index: 'vector_index',
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        path: 'plot_embedding_voyage_3_large',
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        queryVector: 'redacted',
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        numCandidates: 150,
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        limit: 10,
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        explain: {
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          query: {
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            type: 'WrappedKnnQuery',
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            args: {
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              query: [
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                {
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                  type: 'InstrumentableKnnFloatVectorQuery',
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                  args: {
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                    field: '$type:knnVector/plot_embedding_voyage_3_large',
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                    k: 150
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                  },
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                  stats: {
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                    context: { millisElapsed: 0 },
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                    match: { millisElapsed: 0 },
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                    score: { millisElapsed: 0 }
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                  }
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                },
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                {
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                  type: 'DocAndScoreQuery',
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                  args: {},
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                  stats: {
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                    context: {
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                      millisElapsed: 1.378949,
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                      invocationCounts: {
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                        createWeight: Long('1'),
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                        createScorer: Long('4')
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                      }
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                    },
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                    match: {
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                      millisElapsed: 0.341389,
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                      invocationCounts: { nextDoc: Long('152') }
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                    },
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                    score: {
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                      millisElapsed: 0.205415,
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                      invocationCounts: {
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                        score: Long('150'),
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                        setMinCompetitiveScore: Long('26')
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                      }
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                    }
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                  }
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                }
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              ]
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            },
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            stats: {
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              context: {
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                millisElapsed: 57.285674,
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                invocationCounts: {
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                  vectorExecution: Long('1'),
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                  createWeight: Long('1'),
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                  createScorer: Long('4')
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                }
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              },
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              match: {
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                millisElapsed: 0.341389,
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                invocationCounts: { nextDoc: Long('152') }
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              },
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              score: {
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                millisElapsed: 0.205415,
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                invocationCounts: {
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                  score: Long('150'),
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                  setMinCompetitiveScore: Long('26')
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                }
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              }
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            }
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          },
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          collectors: {
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            allCollectorStats: {
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              millisElapsed: 0.840381,
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              invocationCounts: {
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                collect: Long('150'),
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                competitiveIterator: Long('2'),
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                setScorer: Long('2')
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              }
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            }
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          },
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          metadata: {
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            mongotVersion: '1.54.0',
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            mongotHostName: '<hostname>.mongodb.net',
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            indexName: 'vector_index',
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            lucene: { totalSegments: 2, totalDocs: 3483 }
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          },
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          resourceUsage: {
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            majorFaults: Long('0'),
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            minorFaults: Long('0'),
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            userTimeMs: Long('0'),
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            systemTimeMs: Long('0'),
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            maxReportingThreads: 1,
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            numBatches: 1
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          },
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          luceneVectorSegmentStats: [
101
            {
102
              id: '_0',
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              executionType: 'Approximate',
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              docCount: 1952,
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              approximateStage: { millisElapsed: 32.916505 }
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            },
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            {
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              id: '_1',
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              executionType: 'Approximate',
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              docCount: 1531,
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              approximateStage: { millisElapsed: 8.661519 }
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            }
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          ]
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        }
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      },
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      nReturned: Long('10'),
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      executionTimeMillisEstimate: Long('256')
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    },
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    {
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      '$_internalSearchIdLookup': {
121
        limit: Long('10'),
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        subPipeline: [
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          { '$match': { _id: { '$eq': '_id placeholder' } } }
124
        ],
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        totalDocsExamined: Long('10'),
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        totalKeysExamined: Long('10'),
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        numDocsFilteredByIdLookup: Long('0')
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      },
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      nReturned: Long('10'),
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      executionTimeMillisEstimate: Long('256')
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    }
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  ],
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  queryShapeHash: '2E39BED257F2B59D3F8652E1A81A18B1140602C4E253DED9FE208D584EA00083',
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  serverInfo: {
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    host: '<hostname>.mongodb.net',
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    port: 27017,
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    version: '8.2.1-rc1',
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    gitVersion: '3312bdcf28aa65f5930005e21c2cb130f648b8c3'
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  },
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  serverParameters: {
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    internalQueryFacetBufferSizeBytes: 104857600,
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    internalQueryFacetMaxOutputDocSizeBytes: 104857600,
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    internalLookupStageIntermediateDocumentMaxSizeBytes: 104857600,
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    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
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    internalQueryMaxBlockingSortMemoryUsageBytes: 104857600,
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    internalQueryProhibitBlockingMergeOnMongoS: 0,
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    internalQueryMaxAddToSetBytes: 104857600,
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    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600,
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    internalQueryFrameworkControl: 'trySbeRestricted',
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    internalQueryPlannerIgnoreIndexWithCollationForRegex: 1
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  },
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  command: {
153
    aggregate: 'embedded_movies',
154
    pipeline: [
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      {
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        '$vectorSearch': {
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          index: 'vector_index',
158
          path: 'plot_embedding_voyage_3_large',
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          queryVector: [
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            -0.034731735,  0.008558298,   -0.0153717, -0.029912498,  0.011549547,
161
            ...,
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            -0.006688767,  0.047527634,  0.040714234
163
          ],
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          numCandidates: 150,
165
          limit: 10
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        }
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      }
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    ],
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    cursor: {},
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    '$db': 'sample_mflix'
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  },
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  ok: 1,
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  '$clusterTime': {
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    clusterTime: Timestamp({ t: 1759341228, i: 32 }),
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    signature: {
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      hash: Binary.createFromBase64('BsaUr/khHU1Fyl5/g8htqoavlU8=', 0),
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      keyId: Long('7553982574624768005')
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    }
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  },
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  operationTime: Timestamp({ t: 1759341228, i: 32 })
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}

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  explainVersion: '1',
  stages: [
    {
      '$vectorSearch': {
        index: 'vector_index',
        path: 'plot_embedding_voyage_3_large',
        queryVector: 'redacted',
        exact: true,
        limit: 10,
        explain: {
          query: {
            type: 'ExactVectorSearchQuery',
            args: {
              field: '$type:knnVector/plot_embedding_voyage_3_large',
              similarityFunction: 'dotProduct',
              filter: {
                type: 'DefaultQuery',
                args: { queryType: 'FieldExistsQuery' },
                stats: {
                  context: {
                    millisElapsed: 0.756254,
                    invocationCounts: {
                      createWeight: Long('1'),
                      createScorer: Long('4')
                    }
                  },
                  match: {
                    millisElapsed: 3.835071,
                    invocationCounts: { nextDoc: Long('3405') }
                  },
                  score: { millisElapsed: 0 }
                }
              }
            },
            stats: {
              context: {
                millisElapsed: 1.271846,
                invocationCounts: { createWeight: Long('1'), createScorer: Long('4') }
              },
              match: {
                millisElapsed: 7.699638,
                invocationCounts: { nextDoc: Long('3405') }
              },
              score: {
                millisElapsed: 139.077653,
                invocationCounts: {
                  score: Long('3403'),
                  setMinCompetitiveScore: Long('63')
                }
              }
            }
          },
          collectors: {
            allCollectorStats: {
              millisElapsed: 146.798572,
              invocationCounts: {
                collect: Long('3403'),
                competitiveIterator: Long('2'),
                setScorer: Long('2')
              }
            }
          },
          metadata: {
            mongotVersion: '1.54.0',
            mongotHostName: '<hostname>.mongodb.net',
            indexName: 'vector_index',
            lucene: { totalSegments: 2, totalDocs: 3483 }
          },
          resourceUsage: {
            majorFaults: Long('0'),
            minorFaults: Long('0'),
            userTimeMs: Long('0'),
            systemTimeMs: Long('0'),
            maxReportingThreads: 1,
            numBatches: 1
          }
        }
      },
      nReturned: Long('10'),
      executionTimeMillisEstimate: Long('208')
    },
    {
      '$_internalSearchIdLookup': {
        limit: Long('10'),
        subPipeline: [
          { '$match': { _id: { '$eq': '_id placeholder' } } }
        ],
        totalDocsExamined: Long('10'),
        totalKeysExamined: Long('10'),
        numDocsFilteredByIdLookup: Long('0')
      },
      nReturned: Long('10'),
      executionTimeMillisEstimate: Long('208')
    }
  ],
  queryShapeHash: '2E39BED257F2B59D3F8652E1A81A18B1140602C4E253DED9FE208D584EA00083',
  serverInfo: {
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    port: 27017,
    version: '8.2.1-rc1',
    gitVersion: '3312bdcf28aa65f5930005e21c2cb130f648b8c3'
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    internalQueryFacetMaxOutputDocSizeBytes: 104857600,
    internalLookupStageIntermediateDocumentMaxSizeBytes: 104857600,
    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
    internalQueryMaxBlockingSortMemoryUsageBytes: 104857600,
    internalQueryProhibitBlockingMergeOnMongoS: 0,
    internalQueryMaxAddToSetBytes: 104857600,
    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600,
    internalQueryFrameworkControl: 'trySbeRestricted',
    internalQueryPlannerIgnoreIndexWithCollationForRegex: 1
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  command: {
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    pipeline: [
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          index: 'vector_index',
          path: 'plot_embedding_voyage_3_large',
          queryVector: [
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            ...,
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          ],
          exact: true,
          limit: 10
        }
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    ],
    cursor: {},
    '$db': 'sample_mflix'
  },
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  '$clusterTime': {
    clusterTime: Timestamp({ t: 1759341655, i: 1 }),
    signature: {
      hash: Binary.createFromBase64('/pUN/IbVV/OKyakbZcIug8HRS8M=', 0),
      keyId: Long('7553982574624768005')
    }
  },
  operationTime: Timestamp({ t: 1759341655, i: 1 })
}

{
  explainVersion: '1',
  stages: [
    {
      '$vectorSearch': {
        index: 'vector_index',
        path: 'plot_embedding_voyage_3_large',
        queryVector: 'redacted',
        numCandidates: 150,
        limit: 10,
        explain: {
          query: {
            type: 'WrappedKnnQuery',
            args: {
              query: [
                {
                  type: 'InstrumentableKnnFloatVectorQuery',
                  args: {
                    field: '$type:knnVector/plot_embedding_voyage_3_large',
                    k: 150
                  }
                },
                { type: 'DocAndScoreQuery', args: {} }
              ]
            }
          },
          metadata: {
            mongotVersion: '1.54.0',
            mongotHostName: '<hostname>.mongodb.net',
            indexName: 'vector_index',
            lucene: { totalSegments: 2, totalDocs: 3483 }
          }
        }
      }
    },
    {
      '$_internalSearchIdLookup': {
        limit: Long('10'),
        subPipeline: [
          { '$match': { _id: { '$eq': '_id placeholder' } } }
        ]
      }
    }
  ],
  queryShapeHash: '2E39BED257F2B59D3F8652E1A81A18B1140602C4E253DED9FE208D584EA00083',
  serverInfo: {
    host: '<hostname>.mongodb.net',
    port: 27017,
    version: '8.2.1-rc1',
    gitVersion: '3312bdcf28aa65f5930005e21c2cb130f648b8c3'
  },
  serverParameters: {
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    internalQueryFacetMaxOutputDocSizeBytes: 104857600,
    internalLookupStageIntermediateDocumentMaxSizeBytes: 104857600,
    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
    internalQueryMaxBlockingSortMemoryUsageBytes: 104857600,
    internalQueryProhibitBlockingMergeOnMongoS: 0,
    internalQueryMaxAddToSetBytes: 104857600,
    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600,
    internalQueryFrameworkControl: 'trySbeRestricted',
    internalQueryPlannerIgnoreIndexWithCollationForRegex: 1
  },
  command: {
    aggregate: 'embedded_movies',
    pipeline: [
      {
        '$vectorSearch': {
          index: 'vector_index',
          path: 'plot_embedding_voyage_3_large',
          queryVector: [
            -0.034731735,  0.008558298,   -0.0153717, -0.029912498,  0.011549547,
            ...,
            -0.006688767,  0.047527634,  0.040714234
          ],
          numCandidates: 150,
          limit: 10
        }
      }
    ],
    cursor: {},
    '$db': 'sample_mflix'
  },
  ok: 1,
  '$clusterTime': {
    clusterTime: Timestamp({ t: 1759341765, i: 1 }),
    signature: {
      hash: Binary.createFromBase64('rPjwbtfbjVrbcvkkN0ct/b1UYa8=', 0),
      keyId: Long('7553982574624768005')
    }
  },
  operationTime: Timestamp({ t: 1759341765, i: 1 })
}

{
  explainVersion: '1',
  stages: [
    {
      '$vectorSearch': {
        index: 'vector_index',
        path: 'plot_embedding_voyage_3_large',
        queryVector: 'redacted',
        exact: true,
        limit: 10,
        explain: {
          query: {
            type: 'ExactVectorSearchQuery',
            args: {
              field: '$type:knnVector/plot_embedding_voyage_3_large',
              similarityFunction: 'dotProduct',
              filter: {
                type: 'DefaultQuery',
                args: { queryType: 'FieldExistsQuery' }
              }
            }
          },
          metadata: {
            mongotVersion: '1.54.0',
            mongotHostName: '<hostname>.mongodb.net',
            indexName: 'vector_index',
            lucene: { totalSegments: 2, totalDocs: 3483 }
          }
        }
      }
    },
    {
      '$_internalSearchIdLookup': {
        limit: Long('10'),
        subPipeline: [
          { '$match': { _id: { '$eq': '_id placeholder' } } }
        ]
      }
    }
  ],
  queryShapeHash: '2E39BED257F2B59D3F8652E1A81A18B1140602C4E253DED9FE208D584EA00083',
  serverInfo: {
    host: '<hostname>.mongodb.net',
    port: 27017,
    version: '8.2.1-rc1',
    gitVersion: '3312bdcf28aa65f5930005e21c2cb130f648b8c3'
  },
  serverParameters: {
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    internalQueryFacetMaxOutputDocSizeBytes: 104857600,
    internalLookupStageIntermediateDocumentMaxSizeBytes: 104857600,
    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
    internalQueryMaxBlockingSortMemoryUsageBytes: 104857600,
    internalQueryProhibitBlockingMergeOnMongoS: 0,
    internalQueryMaxAddToSetBytes: 104857600,
    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600,
    internalQueryFrameworkControl: 'trySbeRestricted',
    internalQueryPlannerIgnoreIndexWithCollationForRegex: 1
  },
  command: {
    aggregate: 'embedded_movies',
    pipeline: [
      {
        '$vectorSearch': {
          index: 'vector_index',
          path: 'plot_embedding_voyage_3_large',
          queryVector: [
            -0.034731735,  0.008558298,   -0.0153717, -0.029912498,  0.011549547,
            ...,
            -0.006688767,  0.047527634,  0.040714234
          ],
          exact: true,
          limit: 10
        }
      }
    ],
    cursor: {},
    '$db': 'sample_mflix'
  },
  ok: 1,
  '$clusterTime': {
    clusterTime: Timestamp({ t: 1759342075, i: 1 }),
    signature: {
      hash: Binary.createFromBase64('jQiwcAMEmfzFnVU/pyb29TnYu0w=', 0),
      keyId: Long('7553982574624768005')
    }
  },
  operationTime: Timestamp({ t: 1759342075, i: 1 })
}

{
  explainVersion: '1',
  stages: [
    {
      '$vectorSearch': {
        index: 'vector_index',
        path: 'plot_embedding_voyage_3_large',
        queryVector: 'redacted',
        numCandidates: 150,
        limit: 10,
        explain: {
          query: {
            type: 'WrappedKnnQuery',
            args: {
              query: [
                {
                  type: 'InstrumentableKnnFloatVectorQuery',
                  args: {
                    field: '$type:knnVector/plot_embedding_voyage_3_large',
                    k: 150
                  },
                  stats: {
                    context: { millisElapsed: 0 },
                    match: { millisElapsed: 0 },
                    score: { millisElapsed: 0 }
                  }
                },
                {
                  type: 'DocAndScoreQuery',
                  args: {},
                  stats: {
                    context: {
                      millisElapsed: 0.013013,
                      invocationCounts: {
                        createWeight: Long('1'),
                        createScorer: Long('4')
                      }
                    },
                    match: {
                      millisElapsed: 0.459619,
                      invocationCounts: { nextDoc: Long('152') }
                    },
                    score: {
                      millisElapsed: 0.179147,
                      invocationCounts: {
                        score: Long('150'),
                        setMinCompetitiveScore: Long('26')
                      }
                    }
                  }
                }
              ]
            },
            stats: {
              context: {
                millisElapsed: 7.113224,
                invocationCounts: {
                  vectorExecution: Long('1'),
                  createWeight: Long('1'),
                  createScorer: Long('4')
                }
              },
              match: {
                millisElapsed: 0.459619,
                invocationCounts: { nextDoc: Long('152') }
              },
              score: {
                millisElapsed: 0.179147,
                invocationCounts: {
                  score: Long('150'),
                  setMinCompetitiveScore: Long('26')
                }
              }
            }
          },
          collectors: {
            allCollectorStats: {
              millisElapsed: 0.868815,
              invocationCounts: {
                collect: Long('150'),
                competitiveIterator: Long('2'),
                setScorer: Long('2')
              }
            }
          },
          metadata: {
            mongotVersion: '1.54.0',
            mongotHostName: '<hostname>.mongodb.net',
            indexName: 'vector_index',
            lucene: { totalSegments: 2, totalDocs: 3483 }
          },
          resourceUsage: {
            majorFaults: Long('0'),
            minorFaults: Long('0'),
            userTimeMs: Long('0'),
            systemTimeMs: Long('0'),
            maxReportingThreads: 1,
            numBatches: 1
          },
          luceneVectorSegmentStats: [
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              id: '_1',
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              approximateStage: { millisElapsed: 2.58089 }
            },
            {
              id: '_0',
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              approximateStage: { millisElapsed: 3.483542 }
            }
          ]
        }
      },
      nReturned: Long('10'),
      executionTimeMillisEstimate: Long('29')
    },
    {
      '$_internalSearchIdLookup': {
        limit: Long('10'),
        subPipeline: [
          { '$match': { _id: { '$eq': '_id placeholder' } } }
        ],
        totalDocsExamined: Long('10'),
        totalKeysExamined: Long('10'),
        numDocsFilteredByIdLookup: Long('0')
      },
      nReturned: Long('10'),
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    }
  ],
  queryShapeHash: '2E39BED257F2B59D3F8652E1A81A18B1140602C4E253DED9FE208D584EA00083',
  serverInfo: {
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    port: 27017,
    version: '8.2.1-rc1',
    gitVersion: '3312bdcf28aa65f5930005e21c2cb130f648b8c3'
  },
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    internalLookupStageIntermediateDocumentMaxSizeBytes: 104857600,
    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
    internalQueryMaxBlockingSortMemoryUsageBytes: 104857600,
    internalQueryProhibitBlockingMergeOnMongoS: 0,
    internalQueryMaxAddToSetBytes: 104857600,
    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600,
    internalQueryFrameworkControl: 'trySbeRestricted',
    internalQueryPlannerIgnoreIndexWithCollationForRegex: 1
  },
  command: {
    aggregate: 'embedded_movies',
    pipeline: [
      {
        '$vectorSearch': {
          index: 'vector_index',
          path: 'plot_embedding_voyage_3_large',
          queryVector: [
            -0.034731735,  0.008558298,   -0.0153717, -0.029912498,  0.011549547,
            ...,
            -0.006688767,  0.047527634,  0.040714234
          ],
          numCandidates: 150,
          limit: 10
        }
      }
    ],
    cursor: {},
    '$db': 'sample_mflix'
  },
  ok: 1,
  '$clusterTime': {
    clusterTime: Timestamp({ t: 1759342175, i: 1 }),
    signature: {
      hash: Binary.createFromBase64('AZZrjVPfyyBofyQq/gzs9UBL+/Q=', 0),
      keyId: Long('7553982574624768005')
    }
  },
  operationTime: Timestamp({ t: 1759342175, i: 1 })
}

{
  explainVersion: '1',
  stages: [
    {
      '$vectorSearch': {
        index: 'vector_index',
        path: 'plot_embedding_voyage_3_large',
        queryVector: 'redacted',
        exact: true,
        limit: 10,
        explain: {
          query: {
            type: 'ExactVectorSearchQuery',
            args: {
              field: '$type:knnVector/plot_embedding_voyage_3_large',
              similarityFunction: 'dotProduct',
              filter: {
                type: 'DefaultQuery',
                args: { queryType: 'FieldExistsQuery' },
                stats: {
                  context: {
                    millisElapsed: 0.037129,
                    invocationCounts: {
                      createWeight: Long('1'),
                      createScorer: Long('4')
                    }
                  },
                  match: {
                    millisElapsed: 1.128957,
                    invocationCounts: { nextDoc: Long('3405') }
                  },
                  score: { millisElapsed: 0 }
                }
              }
            },
            stats: {
              context: {
                millisElapsed: 0.061268,
                invocationCounts: { createWeight: Long('1'), createScorer: Long('4') }
              },
              match: {
                millisElapsed: 2.531393,
                invocationCounts: { nextDoc: Long('3405') }
              },
              score: {
                millisElapsed: 7.956341,
                invocationCounts: {
                  score: Long('3403'),
                  setMinCompetitiveScore: Long('63')
                }
              }
            }
          },
          collectors: {
            allCollectorStats: {
              millisElapsed: 10.004281,
              invocationCounts: {
                collect: Long('3403'),
                competitiveIterator: Long('2'),
                setScorer: Long('2')
              }
            }
          },
          metadata: {
            mongotVersion: '1.54.0',
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