Mongo how many collections

In the end we decided to give comments their own collection and to embed the replies inside the relevant comment document. Since I am bringing up embedding you should know about some issues that can cause as we have learned in the past few weeks. The big advantage is that To work around this you need to write some logic in your app layer that will go through the embedded documents and update them accordingly we use mongo bulk updates to do this. This of course can be very heavy depending on how many documents you have to update.

So again, it all goes back to how often you will need to be doing updates vs reads. Just want to add to my last comment there are some issues in how meteor handles updates to embedded documents which also needs to be taken into consideration. Each day's readings are stored in a separate collection, named by the reading date:. With each passing day, the number of collections in the database increments. Since the number of collections is unbounded, there is an ever-growing need from the database to maintain these collections and their corresponding indexes.

If the database eventually reaches a point where it is managing thousands of collections and indexes, it may result in performance degradation. Additionally, this approach does not easily facilitate queries across multiple days. This value indicates the maximum size of the collection in bytes.

The basic syntax of this command is shown below:. This command selects the database employee. We can verify that this operation was successful using the command shown below: db. Now that we have a collection stored in a database, we can finally test out the show collections command. In this article, we created a sample collection and then used the show collections command to retrieve its name. The default limit on memory usage for createIndexes is megabytes for versions 4.

Setting a higher memory limit may result in faster completion of index builds. However, setting this limit too high relative to the unused RAM on your system can result in memory exhaustion and server shutdown.

Index builds may be initiated either by a user command such as Create Index or by an administrative process such as an initial sync. An initial sync operation populates only one collection at a time and has no risk of exceeding the memory limit.

However, it is possible for a user to start index builds on multiple collections in multiple databases simultaneously and potentially consume an amount of memory greater than the limit set in maxIndexBuildMemoryUsageMegabytes.

To minimize the impact of building an index on replica sets and sharded clusters with replica set shards, use a rolling index build procedure as described on Rolling Index Builds on Replica Sets. The following index types only support simple binary comparison and do not support collation :. If you specify a maximum number of documents for a capped collection using the max parameter to create , the limit must be less than 2 32 documents.

If you do not specify a maximum number of documents when creating a capped collection, there is no limit on the number of documents. Replica sets can have up to 7 voting members. For replica sets with more than 7 total members, see Non-Voting Members. If you do not explicitly specify an oplog size i. This is uncommon in un-sharded collections. The geoSearch command is not supported in sharded environments. Starting in MongoDB 3. In previous versions, an index cannot cover a query on a sharded collection when run against a mongos.

An existing collection can only be sharded if its size does not exceed specific limits. These limits can be estimated based on the average size of all shard key values, and the configured chunk size. These limits only apply for the initial sharding operation. Sharded collections can grow to any size after successfully enabling sharding.

If maxCollectionSize is less than or nearly equal to the target collection, increase the chunk size to ensure successful initial sharding. If there is doubt as to whether the result of the calculation is too 'close' to the target collection size, it is likely better to increase the chunk size. After successful initial sharding, you can reduce the chunk size as needed.

If you later reduce the chunk size, it may take time for all chunks to split to the new size. This table illustrates the approximate maximum collection sizes using the formulas described above:. MongoDB does not support unique indexes across shards, except when the unique index contains the full shard key as a prefix of the index. In these situations MongoDB will enforce uniqueness across the full key, not a single field.

Unique Constraints on Arbitrary Fields for an alternate approach.