What is a sparse index in MongoDB?

What is a sparse index in MongoDB?

Sparse indexes only contain entries for documents that have the indexed field, even if the index field contains a null value. The index skips over any document that is missing the indexed field. The index is “sparse” because it does not include all documents of a collection.

What is sparse index?

Sparse indexing allows you to specify the conditions under which a pointer segment is suppressed, not generated, and put in the index database. Sparse indexing has two advantages. The primary one is that it reduces the size of the index, saving space and decreasing maintenance of the index.

What is the difference between dense and sparse index?

Dense Index: It has index entries for every search key value (and hence every record) in the database file. The dense index can be built on order as well as unordered fields of the database files. Sparse Index: It has index entries for only some of the search key values/records in the database file.

What is TTL index in MongoDB?

TTL indexes are special single-field indexes that MongoDB can use to automatically remove documents from a collection after a certain amount of time or at a specific clock time.

What is sparse index in SQL?

An SQL sparse index is like a select/omit access path. Both the sparse index and the select/omit logical file contain only keys that meet the selection specified. For a sparse index, the selection is specified with a WHERE clause.

What is a clustered index?

Clustered indexes are indexes whose order of the rows in the data pages corresponds to the order of the rows in the index. This order is why only one clustered index can exist in any table, whereas, many non-clustered indexes can exist in the table.

Is primary index sparse or dense?

So a primary index has to be dense to work, a secondary index can be either dense or sparse depending on need. A dense index is using more space to store data, while a sparse index is slower. secondary indexes can be dense or sparse.

What is the advantage of sparse index over dense index?

Sparse indexing has two advantages. The primary one is that it reduces the size of the index, saving space and decreasing maintenance of the index. By decreasing the size of the index, performance is improved. The second advantage is that you do not need to generate unnecessary index entries.

Which is faster sparse or dense index?

Dense indices are faster in general, but sparse indices require less space and impose less maintenance for insertions and deletions.

What is capped in MongoDB?

Capped collections restrict updates to the documents if the update results in increased document size. Since capped collections store documents in the order of the disk storage, it ensures that the document size does not increase the size allocated on the disk.

How does MongoDB store time series data?

As of MongoDB 5.0, MongoDB natively supports time series data. You can create a new time series collection with the createCollection() command. When you want to create a time series collection, you must include the timeField option. timeField indicates the name of the field that includes the date in each document.

What is sparse database?

Sparse data is a variable in which the cells do not contain actual data within data analysis. Sparse data is empty or has a zero value. Sparse data is different from missing data because sparse data shows up as empty or zero while missing data doesn’t show what some or any of the values are.

Can a secondary index be sparse?

Can a sparse index be used as a non clustered index?

There is at most one sparse index since it is not possible to build sparse index that is not clustered. (i) Index table is small and hence save memory space (especially in large files).

Is primary indexing sparse or dense?

dense
So a primary index has to be dense to work, a secondary index can be either dense or sparse depending on need. A dense index is using more space to store data, while a sparse index is slower. secondary indexes can be dense or sparse. Dense uses more storage but is faster.

What is capped and uncapped collection in MongoDB?

Capped collections are fixed-size collections means when we create the collection, we must fix the maximum size of the collection(in bytes) and the maximum number of documents that it can store.

What is sharding in MongoDB?

Sharding is the process of distributing data across multiple hosts. In MongoDB, sharding is achieved by splitting large data sets into small data sets across multiple MongoDB instances.

Is MongoDB good for time series?

From the very beginning, developers have been using MongoDB to store time-series data. MongoDB can be an extremely efficient engine for storing and processing time-series data, but you’d have to know how to correctly model it to have a performant solution, but that wasn’t as straightforward as it could have been.