How does Sharding improve performance in MongoDB?

Sharding a Collection to Distribute Data As your application grows, the data in your MongoDB database increases as well. When you shard a MongoDB collection, the data is split across multiple server instances. This way, the same node is not queried in succession.

How does MongoDB maintain concurrency?

MongoDB uses multi-granularity locking(see wired tiger) that allows operations to lock at the global, database or collection level, and allows for individual storage engines to implement their own concurrency control below the collection level (e.g., at the document-level in WiredTiger).

Does Sharding increase performance?

Database sharding provides a method for scalability across independent servers, each with its own CPU, memory and disk. The technique allows the proper balancing of database size with system resources, resulting in dramatic performance improvements and scalability for a given application.

How does the granularity of data items affect the performance of concurrency control?

The multiple granularity locking protocol increases concurrency and decreases overhead especially when there is a combination of short transactions with a few accesses and transactions that last for a long time accessing a large number of objects such as audit transactions that access every item in the database.

What are the benefits of Sharding in MongoDB?

Advantages of Sharding MongoDB distributes the read and write workload across the shards in the sharded cluster, allowing each shard to process a subset of cluster operations. Both read and write workloads can be scaled horizontally across the cluster by adding more shards.

Is MongoDB single threaded?

The MongoDB C driver has two connection modes: single-threaded and pooled.

What is aggregation in MongoDB?

In MongoDB, aggregation operations process the data records/documents and return computed results. It collects values from various documents and groups them together and then performs different types of operations on that grouped data like sum, average, minimum, maximum, etc to return a computed result.

What is the disadvantage of locking?

Locking has a few other disadvantages. When a thread is waiting for a lock, it cannot do anything else. If a thread holding a lock is permanently blocked (due to an infinite loop, deadlock, livelock, or other liveness failure), any threads waiting for that lock can never make progress.

What factors affect selection of granularity size for data items?

What factors which affect the selection of granularity size of…

• A database record.
• A field value of a database record.
• A disk block.
• A whole file.
• The whole database.