Point out the correct statement.
1.For $geoSphere queries that specify GeoJSON geometries with areas greater than a single hemisphere, the use of the default CRS results in queries for the complementary geometries
2.When determining inclusion, MongoDB considers the border of a shape to be part of the shape, subject to the precision of floating point numbers
3.The custom MongoDB CRS uses a anti-clockwise winding order
4.None of the mentioned
Answer:2
Posted Date:-2022-01-26 01:42:44
1.smaller
2.bigger
3.equal
4.All of the Mentioned
Answer 11.getallIndexes()
2.getretIndexes()
3.getIndexes()
4. none of the mentioned
Answer 31. union
2. addition
3.intersection
4.All of the Mentioned
Answer 31.compound
2.composite
3. candidate
4.None of the mentioned
Answer 11.For $geoSphere queries that specify GeoJSON geometries with areas greater than a single hemisphere, the use of the default CRS results in queries for the complementary geometries
2.When determining inclusion, MongoDB considers the border of a shape to be part of the shape, subject to the precision of floating point numbers
3.The custom MongoDB CRS uses a anti-clockwise winding order
4.None of the mentioned
Answer 21.MongoDB can return sorted results by using the ordering in the index
2.MongoDB defines indexes at the collection level and supports indexes on any field or sub-field of the documents in a MongoDB collection
3.Fundamentally, indexes in MongoDB is different to indexes in other database systems
4.None of the mentioned
Answer 31. You may not create compound indexes that have hashed index fields
2.The order of the fields in a compound index is very important
3.You will receive a warning if you attempt to create a compound index that includes a hashed index
4. none of the mentioned
Answer 31. dropIndex()
2.modIndex()
3.createIndex()
4.None of the mentioned
Answer 31. primary
2.root
3.hash
4.All of the Mentioned
Answer 31.2dsph
2.2d
3.geoHaystack
4.All of the Mentioned
Answer 21.$withing
2.$gwithin
3.$within
4.All of the Mentioned
Answer 31.Hashed
2.Unique
3.Sparse
4. Compound
Answer 41. 2.1
2.2.4
3. 3.0
4.2.2
Answer 41.Hashed
2.Unique
3.Multikey
4.compound
Answer 41.db.collection.Index()
2.db.collection.reIndex()
3.db.collection.rebuildIndex()
4.None of the mentioned
Answer 11. $geokey
2.$geoin
3.$geoWithin
4. All of the mentioned
Answer 31.union
2.intersection
3.projection
4.None of the mentioned
Answer 21. string
2. text
3. char
4.None of the mentioned
Answer 21.2dsphere
2. 2d
3.geoHaystack
4.All of the Mentioned
Answer 11.Single
2.Non Unique
3.Compound
4.none of the mentioned
Answer 11.singlekey
2.multikey
3.compkey
4.None of the mentioned
Answer 21.primary
2. secondary
3. upadte
4. none of the mentioned
Answer 11. If an appropriate index exists for a query, MongoDB cannot use the index to limit the number of documents it must inspect
2.Indexes support the efficient execution of queries in MongoDB
3.The index stores the location of a specific field or set of fields, ordered by the value of the field
4.None of the mentioned
Answer 21. Whether the use of a compound index or the use of an index intersection is more efficient depends on the particular query and the system
2. Certain restrictions apply to indexes, such as the length of the index keys or the number of indexes per collection
3. For queries that specify compound query conditions, if one index can fulfill a part of a query condition, and another index can fulfill another part of the query condition, then MongoDB can use the i
4.None of the mentioned
Answer 41.If you build a TTL index in the foreground, MongoDB does not remove expired documents as soon as the index finishes building
2.The TTL index does guarantee that expired data will be deleted immediately upon expiration
3.Duration of the removal operation depends on the workload of your mongod instance
4.None of the mentioned
Answer 31.After 4.0, you cannot terminate both background index builds and foreground index builds
2. Before MongoDB 2.1, you could only terminate background index builds
3.After 2.4, you can terminate both background index builds and foreground index builds
4.None of the mentioned
Answer 31.TTL index is ideal for certain types of information like machine generated event data, logs, and session information that only need to persist in a database for a finite amount of time
2. You cannot combine the sparse index option with the unique index option
3.TTL indexes are special indexes that MongoDB can use to automatically remove documents from a collection after a certain amount of time
4. none of the mentioned
Answer 21.You can create indexes on fields within embedded documents
2.Indexes on embedded fields are similar to indexes on embedded documents
3.Indexes on embedded fields allow you to use a “dot notation,” to introspect into embedded documents
4.None of the mentioned
Answer 31.MongoDB can query for locations contained entirely within a specified polygon
2.MongoDB require an index for inclusion queries; however, such indexes will improve query performance
3. Indexes on embedded fields allow you to use a “dot notation,” to introspect into embedded documents
4. none of the mentioned
Answer 21. The unique constraint applies to separate documents in the collection
2.Unique index prevents separate documents from having the same value for the indexed key
3. Index does prevent a document from having multiple elements or embedded documents in an indexed array from having the same value
4. none of the mentioned
Answer 31.To modify an existing index, you need to drop and recreate the index
2.Your client library may have a different or additional interface for this operation
3.To see the status of an indexing process, you can use the db.statusOp() method in the mongo shell
4.None of the mentioned
Answer 31.If $near or $nearSphere query specifies the center point as a GeoJSON point, specify the distance as a non-negative number in meters
2. If $nearSphere query specifies the center point as legacy coordinate pair, specify the distance as a non-negative number in radians
3.$near can only use the 2dsphere index if the query specifies the center point as a GeoJSON point
4.None of the mentioned
Answer 41.GeoBSON
2.GeoJSON
3.geoJSONB
4.All of the Mentioned
Answer 21.$unique
2. $natural
3.$spatial
4.All of the Mentioned
Answer 21.$sphere
2.$geoin
3.$geometry
4.All of the Mentioned
Answer 31.15
2.45
3.60
4.120
Answer 31.WGS88
2.WGS84
3.JGS88
4. none of the mentioned
Answer 21._id
2.$default
3. _def
4.None of the mentioned
Answer 11.Hashed
2.Unique
3. Sparse
4.None of the mentioned
Answer 31.Hashed
2.Unique
3.Multikey
4.None of the mentioned
Answer 31.$center
2.$maxDistance
3. $minDistance
4. All of the mentioned
Answer 21.2dsphere
2.2d
3.geoHaystack
4.All of the Mentioned
Answer 11. query()
2. find()
3.index()
4. All of the mentioned
Answer 21.CRS
2.CDS
3.CLS
4.None of the mentioned
Answer 11.db.currentOp()
2.db.killOp()
3. db.removeOp()
4. All of the mentioned
Answer 21. $box
2. $circle
3.$shape
4. All of the mentioned
Answer 11.Point
2.LineString
3.MultiPoint
4.None of the mentioned
Answer 41.2dsphere
2.2d
3.geoHaystack
4. All of the mentioned
Answer 41. Hashed
2.Unique
3.Multikey
4.compound
Answer 11.explain()
2.analyze()
3.intersect()
4.None of the mentioned
Answer 11.Hashed
2.Unique
3. Sparse
4. Compound
Answer 31.Hashed
2.Unique
3.Sparse
4.compound
Answer 11.curs.explain()
2.cursor.explain()
3.cursr.explain()
4.All of the Mentioned
Answer 21. Hashed
2.Unique
3.Multikey
4.compound
Answer 31.Hashed
2.Unique
3.Multikey
4.TTL
Answer 41.2d
2.1d
3.3d
4. All of the mentioned
Answer 11.3dsphere
2. 2dsphere
3.1dsphere
4.none of the mentioned
Answer 21.$near
2. $nearsphere
3. $geoIntersect
4.None of the mentioned
Answer 11.$near
2.$nearsphere
3. $geoIntersect
4.None of the mentioned
Answer 31. Hashed
2. Unique
3. Multikey
4.None of the mentioned
Answer 1