I want to shard a collection with data. When I try with sh.shardCollection("myDb.myCollection", {id:"hashed"}) then this collection shard but it's not spread to the whole shards. only spread to the primary shard. for example,
Empty collection after shard,
sh.status() result
Then data add it will spread to whole shards
Collection with data after shard,
sh.status() result
When data add only goes to the primary shard.
My question is how correctly shard a collection with data in MongoDB. Have any other alternative way?
I agree with #Wernfried Domscheit in the comments about the fact that the cluster will take care of distributing the data once the collection is sharded. As mentioned, that is done based on writing to the collection and happens over time. Your test may have too little data or too few writes to trigger the changes.
To your specific question about the initial distribution of chunks, this is covered in the documentation. Applying a hashed shard key on an empty collection in your first example is covered here:
The sharding operation creates empty chunks to cover the entire range of the shard key values and performs an initial chunk distribution. By default, the operation creates 2 chunks per shard and migrates across the cluster. You can use numInitialChunks option to specify a different number of initial chunks. This initial creation and distribution of chunks allows for faster setup of sharding.
And behavior on the collection with data is covered just above it here:
The sharding operation creates the initial chunk(s) to cover the entire range of the shard key values. The number of chunks created depends on the configured chunk size.
Both of these described behaviors match what you have demonstrated in your question.
Related
I am new to mongodb and wish to create a distributed database environment using docker-compose with mongodb. I've created multiple docker with shards to simulate multiple sites. However, I have a problem to replicate the same set of documents into multiple shards.
For example I have a collection with a key that has value "A" and "B". I want to distribute this collection into 2 shards where
Shard 1 = A & B
Shard 2 = B only
However, when I run the balancer it distributes all A's into shard 1 and B's into shard 2. Is there any way I can do the sharding with repeated data or am I using the wrong approach for my problem?
You might be approaching sharding (horizontal scaling) incorrectly. What makes sharding in Mongo work is that the sharding key is chosen such that it results in (vertical) shards which have a roughly even distribution of data, or a similar number of Mongo documents. A requirement of sharding which makes it work well is that queries would typically be directed to only a single shard. If you have queries which need to return some field having the different values of A and B, then it implies that this field should not be the sharding key. Queries can go across shards, but certain cross-shard operations, such as joins, can be very costly. In your particular case, perhaps some other field could be used as sharding key.
Redundancy in MongoDB is provided by replica sets, not sharded clusters.
Each shard can be backed by a replica set with your desired number of nodes to provide the required redundancy level.
It is not possible to have the same document be (authoritatively) located in multiple shards.
For my application I need to shard a fairly big collection, the entire collection will contain app. 500 billion documents.
I have two potential fields which can be used as Sharding Key:
For inserting either Sharding Key will distribute documents evenly throughout the cluster, there is does not matter which field I use as Sharding Key.
For query it is different.
Field(1) is usually part of the query filter condition, thus query would be processed usually on a single shard only.
Field(2) is typically not part of the query filter condition, thus query would be processed over all shards and typically several shards will contribute to final query result.
Which one is the better field to be used as Sharding Key? I did not find anything in MongoDB documentation about that topic.
Either fields have the same range and very similar cardinality figures, there won't be any difference. Usually the number of documents returned by a query is very low (typically less than 20-30 documents).
In a sharded cluster the mongos router determines which shard is to be targeted for a read or write operation - based on the available shard key meta-data stored on the config servers.
For inserting either Sharding Key will distribute documents evenly
throughout the cluster, there is does not matter which field I use as
Sharding Key.
When you insert a document it will have a shard key and the document will be stored on a designated shard.
Field(1) is usually part of the query filter condition, thus query
would be processed usually on a single shard only.
The shard key's main purposes are (a) to distribute data evenly across shards in a cluster, and (b) to be able to query the data in such a way that the query targets a single shard.
For a query to target a single shard, the shard key must be part of the query's filter criteria. The mongos router will target the single shard using the shard key.
If the shard key is not part of the filter criteria it will be a scatter-gather operation (a long running query). It is important that the most important query operations of the application using the sharded collection must be able use the shard key.
Field(2) is typically not part of the query filter condition, thus
query would be processed over all shards and typically several shards
will contribute to final query result.
When the shard key is not part of the query filter, the operation will span across multiple shards (a scatter-gather operation) and it will be a slow running operation. The mongos router will not be able to determine which shards have the target data, and all the shards in the cluster will be queried to return the final result.
Which one is the better field to be used as Sharding Key?
It can be concluded that the Field(1) must be used as a shard key.
See documentation on shard keys and choosing a shard key # MongoDB docs on Shard Keys.
Generally, if a query spreads across multiple shards, it is considered less optimized. It takes more time than reading from single shard.
Does it hold true for writing as well? If I am writing some data and it will distribute among multiple shards, will it be considered less optimized?
If yes, what is the best way to write a batch that should go to different shard?
It depends on the operations, see https://docs.mongodb.com/manual/core/sharded-cluster-query-router/#sharding-mongos-targeted.
All insertOne() operations target to one shard. Each document in the insertMany() array targets to a single shard, but there is no guarantee all documents in the array insert into a single shard.
All updateOne(), replaceOne() and deleteOne() operations must include the shard key or _id in the query document. MongoDB returns an error if these methods are used without the shard key or _id.
Depending on the distribution of data in the cluster and the selectivity of the query, mongos may still perform a broadcast operation to fulfill these queries.
use vsm;
sh.enableSharding('vsm');
sh.shardCollection('vsm.pricelist', {maker_id:1});
Ok, we enabled sharding for Database (vsm) and collection in this database (pricelist).
We trying to write about 80 million documents to 'pricelist' collection.
And we have about 2000 distributed uniformly different maker_ids.
We have three shards. And Shard002 is PRIMARY for 'vsm' database.
We write to 'pricelist' collection from four application nodes with started mongos on each.
And during write data to 'pricelist' collection we see CPU Usage 100% ONLY on Shard002 !
We see rebalancing process. And data migrate to Shard000 and Shard003. But Shard002 has hight CPU Usage and Load Average!
Shards deployed on c4.xlarge EBS Optimized instances. dbdata stored on io1 with 2000 IOPS EBS Volumes.
It is looks like MongoDB write data only to one Shard :( What we do wrong?
The problem
What you describe is usually the indication that you have chosen a poor shard key with makerid, most likely monotonically increasing.
What usually happens is that one shard is assigned the key range from x to infinity (shard002 in your case). Now all new documents get written to that shard, until that shards holds more chunks in excess of the current migration threshold. Now the balancer kicks in and moves some chunks. Problem is that new documents still get written to said shard.
The solution
An easy solution for that problem is to use hashed keys for sharding
Now here comes the serious problem: you can not change the shard key.
So what you have to do is to make a backup of the sharded collection, drop it, reshard the collection using the hashed makerId and restore the backup into the new collection.
Is MongoDB always write to primary Shard and then rebalance?
Yes, if you are relying on auto balancer. And loading huge amounts of data into an empty collection
In your situation, you are relying on the autobalancer to do all the sharding / balancing stuff. I assume what you require is, as your data gets loaded it goes to each shard during load hence having less CPU usage etc.
This how sharding / autobalancing will take place on a high level.
Create chunks of data using split http://docs.mongodb.org/manual/reference/command/split/
Move the chunks to other shards http://docs.mongodb.org/manual/reference/command/moveChunk/#dbcmd.moveChunk
Now, when autobalancer is ON these two steps occur when your data is already loaded or loading.
Solution
Create empty collection. Execute the shard command on it. The collection where your data is going to get loaded.
Turn off the auto balancer http://docs.mongodb.org/manual/tutorial/manage-sharded-cluster-balancer/#disable-the-balancer
Manually create empty chunks using split. http://docs.mongodb.org/manual/tutorial/create-chunks-in-sharded-cluster/
Move those empty chunks to different shards. http://docs.mongodb.org/manual/tutorial/migrate-chunks-in-sharded-cluster/
Start the load, This time all your data should go directly to their respective shards.
Turn ON the balancer. (Once the load is complete) http://docs.mongodb.org/manual/tutorial/manage-sharded-cluster-balancer/#enable-the-balancer
You will have to test this approach using a small data set first. But I guess I have got enough information for you to get started.
I'm documenting about the GridFS and the possibility to shard it among different machines.
Reading the documentation here, the suggested shard key is chunks.files_id. This key will be linked to the _id of the files collection, thus this _id is incremental. Every new file i save in the Grid will have a new incremental _id.
In the O'Reilly "Scaling MongoDB" book the use of an incremental shard key is discouraged to avoid HotSpots (the last shard will receive all the write and read).
what is your suggestion for sharding the GridFS collection?
have anybody experienced the HotSpot problem?
thank you.
You should shard on files_id to keep file chunks together, but you are correct that that will create a hotspot. If you can, use something other than ObjectId for _ids in the fs.files collection (probably MD5s would be better than ObjectIds).
We'll be adding hashing for sharding, which will solve this, but not until at least 2.0.
You can shard gridfs data because gridfs it just two collecttions: chunks and files. And gridfs sharding it's very useful and great thing. About gridfs shard key it's always bad choose random or incremental shard key, because data not evenly distribute across shards. In case of incremental shard key all writes going to the last shard and it growth and once difference between become 10 or more chunks, balancer move data to another shards. Moving data to another shard always difficult task that should be avoided as it possible.
So when you choose shard key you should care about even distribution of data.
Also if you get luck mb author of 'Scaling MongoDB' kristina(great specialist in shard keys) will answer to your question.
Documentation says that in common cases you should choose default index fileId:1,n:1 as shard key:
There are different ways that GridFS
can be sharded, depending on the need.
One common way to shard, based on
pre-existing indexes, is:
"files" collection is not sharded. All
file records will live in 1 shard. It
is highly recommended to make that
shard very resilient (at least 3 node
replica set) "chunks" collection gets
sharded using the existing index
"files_id: 1, n: 1". Some files at the
end of ranges may have their chunks
split across shards, but most files
will be fully contained within the
same shard.
Currently MongoDB as of version 1.8.1 supports only sharding on "file_id" field, because of using md5 to verify the upload, but it doesn't
work across shards yet. So you cannot split single file across shards.
Answer on google group7