If I want to sort by product price, when I apply skip and limit it works if prices are distinct but if they are all the same, pagination breaks (next page result isn't expected, it shows already shown results), as if sorting products is computed differently everytime. So I'm wondering is adding product _id (which is unique) to sort: {product_price:1, product_id:1} correct to ensure that my pagination won't break (so that sort is ordered equally everytime). Is there something else I should be aware?
Thanks
Related
I'm working on my app and I just ran into a dilemma regarding what's the best way to handle indexes for firestore.
I have a query that search for publication in a specify community that contains at least one of the tag and in a geohash range. The index for that query looks like this:
community Ascending tag Ascending location.geohash Ascending
Now if my user doesnt need to filter by tag, I run the query without the arrayContains(tag) which prompt me to create another index:
community Ascending location.geohash Ascending
My question is, is it better to create that second index or, to just use the first one and specifying all possible tags in arrayContains in the query if the user want no filters on tag ?
Neither is pertinently better, but it's a typical space vs time tradeoff.
Adding the extra tags in the query adds some overhead there, but it saves you the (storage) cost for the additional index. So you're trading some small amount of runtime performance for a small amount of space/cost savings.
One thing to check is whether the query with tags can actually run on just the second index, as Firestore may be able to do a zigzag merge join. In that case you could only keep the second, smaller index and save the runtime performance of adding additional clauses, but then get a (similarly small) performance difference on the query where you do specify one or more tags.
I have MongoDB collection with ~100,000,000 records.
On the website, users search for these records with "Refinement search" functionality, where they can filter by multiple criteria:
by country, state, region;
by price range;
by industry;
Also, they can review search results sorted:
by title (asc/desc),
by price (asc/desc),
by bestMatch field.
I need to create indexes to avoid full scan for any of combination above (because users use most of the combinations). Following Equality-Sort-Range rule for creating indexes, I have to create a lot of indexes:
All filter combination × All sortings × All range filters, like the following:
country_title
state_title
region_title
title_price
industry_title
country_title_price
country_industry_title
state_industry_title
...
country_price
state_price
region_price
...
country_bestMatch
state_bestMatch
region_bestMatch
...
In reality, I have more criteria (including equality & range), and more sortings. For example, I have multiple price fields and users can sort by any of that prices, so I have to create all filtering indexes for each price field in case if the user will sort by that price.
We use MongoDB 4.0.9, only one server yet.
Until I had sorting, it was easier, at least I could have one compound index like country_state_region and always include country & state in the query when one searches for a region. But with sorting field at the end, I cannot do it anymore - I have to create all different indexes even for location (country/state/region) with all sorting combinations.
Also, not all products have a price, so I cannot just sort by price field. Instead, I have to create two indexes: {hasPrice: -1, price: 1}, and {hasPrice: -1, price: -1} (here, hasPrice is -1, to have records with hasPrice=true always first, no matter price sort direction).
Currently, I use the NodeJS code to generate indexes similar to the following (that's simplified example):
for (const filterFields of getAllCombinationsOf(['country', 'state', 'region', 'industry', 'price'])) {
for (const sortingField of ['name', 'price', 'bestMatch']) {
const index = {
...(_.fromPairs(filterFields.map(x => [x, 1]))),
[sortingField]: 1
};
await collection.ensureIndex(index);
}
}
So, the code above generates more than 90 indexes. And in my real task, this number is even more.
Is it possible somehow to decrease the number of indexes without reducing the query performance?
Thanks!
Firstly, in MongoDB (Refer: https://docs.mongodb.com/manual/reference/limits/), a single collection can have no more than 64 indexes. Also, you should never create 64 indexes unless there will be no writes or very minimal.
Is it possible somehow to decrease the number of indexes without reducing the query performance?
Without sacrificing either of functionality and query performance, you can't.
Few things you can do: (assuming you are using pagination to show results)
Create a separate (not compound) index on each column and let MongoDB execution planner choose index based on meta-information (cardinality, number, etc) it has. Of course, there will be a performance hit.
Based on your judgment and some analytics create compound indexes only for combinations which will be used most frequently.
Most important - While creating compound indexes you can let off sort column. Say you are filtering based on industry and sorting based on price. If you have a compound index (industry, price) then everything will work fine. But if you have index only on the industry (assuming paginated results), then for first few pages query will be quite fast, but will keep degrading as you move on to next pages. Generally, users don't navigate after 5-6 pages. Also, you have to keep in mind for larger skip values, the query will start to fail because of the 32mb memory limit for sorting. This can be overcome with aggregation (instead of the query) with allowDiskUse enable.
Check for keyset pagination (also called seek method) if that can be used in your use-case.
I am working on a database of Polish verbs and I'd like to find out how to display my results such that each verb conjugation appears in the following order: 1ps (1st person singular), 2ps, 3ps, 1ppl (1st person plural, etc.), 2ppl, 3ppl. It displays fine when I insert documents:
verb "żyć/przeżyć" conjugation as array and nested document
But when I go to perform queries it jumbles all the array elements up, in the first case (I want to see them in order of array indices), and sorts the nested document elements into alphabetical order (whereas I want to see them in the order in which they were inserted).
verb "żyć/przeżyć" conjugation array/document query
This should be an easy one to solve, I hope this comes across as a reasonable beginner's question. I have searched for answers but couldn't find much info on this topic. Any and all help is greatly appreciated!
Cheers,
LC.
Your screenshots highlight two different views in MongoDB Compass.
The Schema view is based on a sampling of multiple documents and the order of the fields displayed cannot be specified. The schema analysis (as at Compass 1.7) lists fields in case-insensitive alphabetical order with the _id field at the top. Since this is an aggregate schema view based on multiple documents, the ordering of fields is not expected to reflect individual document order.
If you want to work with individual documents and field ordering you need to use the Documents view, as per your second screenshot. In addition to displaying the actual documents, this view allows you to include sort and skip options for queries:
Example:
{
shortName: "KITT",
longName: "Knight Industries Two Thousand",
fromZeroToSixty: 2,
year: 1982,
manufacturer: "Pontiac",
/* 25 more fields */
}
Ability to query by at least 20 fields which means that only 10 fields are left unindexed
There's 3 fields (all number) that could be used for sorting (both ways)
This leaves me wondering that how does sites with lots of searchable fields do it: e.g real estate or car sale sites where you can filter by every small detail and can choose between several sort options.
How could I pull this off with MongoDB? How should I index that kind of collection?
Im aware that there are dbs specifically made for searching but there must be general rules of thumb to do this (even if less performant) in every db. Im sure not everybody uses Elasticsearch or similar.
---
Optional reading:
My reasoning is that index could be huge but the index order matters. You'll always make sure that fields that return the least results are first and most generic fields are last in index. However, what if user chooses only generic fields? Should I include non-generic fields to query anyway? How to solve ordering in both ways? Or index intersection saves the day and I should just add 20 different indexes?
text index is your friend.
Read up on it here: https://docs.mongodb.com/v3.2/core/index-text/
In short, it's a way to tell mongodb that you want full text search over a specific field, multiple fields, or all fields (yay!)
To allow text indexing of all fields, use the special symbol $**, and define it of type 'text':
db.collection.createIndex( { "$**": "text" } )
you can also configure it with Case Insensitivity or Diacritic Insensitivity, and more.
To perform text searches using the index, use the $text query helper, see: https://docs.mongodb.com/v3.2/reference/operator/query/text/#op._S_text
Update:
In order to allow user to select specific fields to search on, it's possible to use weights when creating the text-index: https://docs.mongodb.com/v3.2/core/index-text/#specify-weights
If you carefully select your fields' weights, for example using different prime numbers only, and then add the $meta text score to your results you may be able to figure out from the "textScore" which field was matched on this query, and so filter out the results that didn't get a hit from a selected search field.
Read more here: https://docs.mongodb.com/v3.2/tutorial/control-results-of-text-search/
Here's my issue:
I have 2 indexes:
A - product titles only
B - product titles and product descriptions
By default I search index A to categorize products (e.g. most bikes have "bike" in title).
Sometimes there instances where to determine category (which might be a sub-category of something) we need to look at description, mostly to exclude irrelevant results. In order for pagination on search result page to work, I need to get this clean result as one array after running RunQueries().
But it does not work. It basically adds results of both queries, and looks like there's no way to subtract results. Anyone has any ideas?
Tell me if I'm completely missing something but it sounds to me like your trying to include results with product titles that match a certain query and exclude results with a description that matches another query?
If this is the case it seems to me that having 2 indexes is useless, and you can have one index with both product titles and descriptions and then run a full text search query as such:
#title queryA #description -queryB
You can use the same query to search for matches that have a title of queryA AND a description of queryB by simply removing the - symbol.
If this is off base the only other way I could think of doing it is using SphinxQL (I'm not well versed in any of the libraries since support for all the libraries which don't use SphinxQL is being phased out in the future as far as I've read)
Using SphinxQL you could run 2 queries, one which is like
SELECT id FROM indexB WHERE MATCH('#description queryB')
And then run a second query using a the list of ids you got from the first query as such
SELECT id FROM indexA WHERE id NOT IN(id1,id2,id3,...)