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pprint(db.restaurants.find({'grades.grade':'Z'}).explain()["executionStats"])

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# Create multikey index
db.restaurants.create_index('grades.grade', 
                            name='grade')

# List indexes
pprint(db.restaurants.index_information())

aniruddha27

# Query stats for query to find restaurants with grade Z
pprint(db.restaurants.find({'grades.grade':'Z'}).explain()["executionStats"])

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# Drop indexes
db.restaurants.drop_indexes()

aniruddha27

{'allPlansExecution': [],
 'executionStages': {'advanced': 152,
                     'alreadyHasObj': 0,
                     'docsExamined': 152,
                     'executionTimeMillisEstimate': 0,
                     'inputStage': {'advanced': 152,
                                    'direction': 'forward',
                                    'dupsDropped': 0,
                                    'dupsTested': 0,
                                    'executionTimeMillisEstimate': 0,

aniruddha27

# Execution stats for query for all restaurants in Manhattan
pprint(db.restaurants.find({'borough':'Manhattan'}).explain()['executionStats'])

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# Execution stats for query to find all Indian restaurants in Manhattan
pprint(db.restaurants.find({'borough':'Manhattan','cuisine':'Indian'}).explain()['executionStats'])

aniruddha27

# Create Compound index
db.restaurants.create_index([('borough',pymongo.ASCENDING),
                            ('cuisine',pymongo.ASCENDING)],
                            name='borough_cuisine')
# Get indexes
pprint(db.restaurants.index_information())

aniruddha27

# All Indian restaurants in Manhattan
pprint(db.restaurants.find({'borough':'Manhattan','cuisine':'Indian'}).explain()['executionStats'])

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# Drop index
db.restaurants.drop_index('_id_')

# Get indexes
db.restaurants.index_information()