I am using mongodb 3.2.4
When I execute db.mytable.find().explain() The winning plan is 'Collscan'
But when I execute db.mytable.find().hint(_id:1).explain() The winning plan is 'IXscan'
So here comes a question: since _id is the default index of a table, why mongodb does not use this index to query?
An index can be used when there is a filter criteria or a sort operation - when the fields in the index are used in the filter predicate and/or the sort. In your case, the find method doesn't have a filter criteria or a sort - so no index is used, and you can see that in the query plan as a collection scan. It is as expected. But, when you provide a hint to the find method the query optimizer tries to use the index, and in your case it did (and you see it in the query plan as an IXSCAN). In either case, with or the without the hint, the find has to scan all the documents or keys in the index.
The _id has a default unique index, yes, but unless you are using the _id field in the query filter predicate or in a sort, the query cannot use it (or, specify explicitly to use index with a hint). You can verify with the following queries, db.mytable.find( { _id: 123 } ) or db.mytable.find( { } ).sort( { _id: -1 } ) the query planner will show index scan even though you do not specify the hint.
The main purpose of the indexes is to make your queries run fast; it is about query performance. It has to be a query with filter predicate and/or a sort operation to use an index (and the fields used in the filter or sort must be indexed for performance). With the find method, in your case, without any of the two you are just accessing all the documents as they are in the collection and the index is of no use (and the query optimizer shows that in the plan).
Related
I have a MongoDB collection that has about 5 million documents. The data in the documents look something like the following:
{
since: [Some Unix timestamp ie. 1660106561)
team: ["a","b","c]
}
when I run the following query, my mongoDB connection times out:
db.myCollection.find({team: {$nin: ['b']}}).sort({since: -1})
I have the following compound indices on my collection:
[since, team]
Is there anything I can do to prevent this query from timing out?
This query is just very hard to execute, $nin is a none selective query, This means it does not utilize indexes well.
For instance, the inequality operators $nin and $ne are not very selective since they often match a large portion of the index. As a result, in many cases, a $nin or $ne query with an index may perform no better than a $nin or $ne query that must scan all documents in a collection.
Specfically in this context i believe the index is even hurting the query performance, because the index is a multikey index using $nin on it still forces scanning large portions of the index tree, after that the query engine still has to fetch and filter each document to make sure it does not have the B value. performance can get even worse if this is just a toy example and the carnality of values is even greater. essentially forcing the engine to do double work.
I reckon that if you execute this query without any index usage, are alternatively if the "since" date matches the "narutal" order and you can drop the skip, you can get much better performance like this:
db.collection.find({team: {$nin: ['b']}}).sort({$natural: -1}).hint({$natural: 1});
Mind you, any query that needs to scan millions of documents will not have a lightning fast execution speed.
I have a collection product in my DB. Below is one sample document:
{
"sku_id":"12345678",
"priduct_name":"milk",
"product_rank":3,
"product_price": 2.4
}
There are 100k such unique documents in our collection.
I want to query this collection using $in query, as shown below.
db.product.find({"sku_id" :{$in :["12345678","23213"]}}).sort( { product_rank: 1 } )
Our requirement is to search documents based on $in query and sort any field in document(asc or desc).
I have created both forward and reverse index on all fields for this collection.
Note: This sku_id array inside $in query can have 1000+ sku_ids.
My doubt is if I use the filter like $in with an array of sku_id and get the sorted result on any field, will it use the index for sorting or will it sort at query time?
Mongo allows you to find out if a query will use an index. As the find operation returns a cursor you can extend the method chain to include an explain() command which does exactly what you need. (suggest you use db.product.find(...).sort(...).explain('executionStats'))
Will it use the index for sorting or will it sort at query time?
The index created on the product_rank will be used in the query but, not an index on the sku_id alone. Instead create a compound index with both product_rank and sku_id(asc and desc).
Are there any elements within the output of MongoDB's explain("executionStats") that gives an idea or a hint about - whether the query is using a given index for filtering or sorting or for both?
I read the following URLs
Mongodb compound indexes for filtering and sorting on BIG collection [points to below URL and has brief discussion]
https://emptysqua.re/blog/optimizing-mongodb-compound-indexes/ [ this one gives general idea, but the explain output uses older format/elements that don't exist in Mongodb 4.0 that I am using ]
https://docs.mongodb.com/manual/tutorial/sort-results-with-indexes/ [documents how to determine the index and leverage index prefixes, but does show explain output confirming the usage]
From MongoDB Docs:
If MongoDB can use an index scan to obtain the requested sort order,
the result will not include a SORT stage. Otherwise, if MongoDB cannot
use the index to sort, the explain result will include a SORT stage.
Example:
Look at the sample data from sortop collection.
Explain plan for a query without index:
Create Index on the collection:
Run the same query and check SORT stage in explain plan:
So, I read the following definition of indexes from [MongoDB Docs][1].
Indexes support the efficient execution of queries in MongoDB. Without indexes, MongoDB must perform a collection scan, i.e. scan every document in a collection, to select those documents that match the query statement. If an appropriate index exists for a query, MongoDB can use the index to limit the number of documents it must inspect.
Indexes are special data structures that store a small portion of the
collection’s data set in an easy to traverse form. The index stores
the value of a specific field or set of fields, ordered by the value
of the field. The ordering of the index entries supports efficient
equality matches and range-based query operations. In addition,
MongoDB can return sorted results by using the ordering in the index.
I have a sample database with a collection called pets. Pets have the following structure.
{
"_id": ObjectId(123abc123abc)
"name": "My pet's name"
}
I created an index on the name field using the following code.
db.pets.createIndex({"name":1})
What I expect is that the documents in the collection, pets, will be indexed in ascending order based on the name field during queries. The result of this index can potentially reduce the overall query time, especially if a query is strategically structured with available indices in mind. Under that assumption, the following query should return all pets sorted by name in ascending order, but it doesn't.
db.pets.find({},{"_id":0})
Instead, it returns the pets in the order that they were inserted. My conclusion is that I lack a fundamental understanding of how indices work. Can someone please help me to understand?
Yes, it is misunderstanding about how indexes work.
Indexes don't change the output of a query but the way query is processed by the database engine. So db.pets.find({},{"_id":0}) will always return the documents in natural order irrespective of whether there is an index or not.
Indexes will be used only when you make use of them in your query. Thus,
db.pets.find({name : "My pet's name"},{"_id":0}) and db.pets.find({}, {_id : 0}).sort({name : 1}) will use the {name : 1} index.
You should run explain on your queries to check if indexes are being used or not.
You may want to refer the documentation on how indexes work.
https://docs.mongodb.com/manual/indexes/
https://docs.mongodb.com/manual/tutorial/sort-results-with-indexes/
What are the advantages we get from compound indexes. I mean suppose we have a collection, in which I have to index over 2 fields say key1 and key2. How different is it from having a compound index {key1:1, key2:1}. Whats the problem with having 2 separate indexes. Can't mongodb make use of 2 or more indexes to satisfy a query.
As at MongoDB 2.2:
Every query, including update operations, use one and only one index.
The query optimizer selects the index empirically by occasionally running alternate query plans and by selecting the plan with the best response time for each query type.
An exception to the above rule is $or queries; each clause is executed in parallel and can use a separate index.
For more information see:
Indexing Overview
Query Optimizer
Explain