It doesn’t. First, a database is a collection of related data, so I assume you mean DBMS or database language.
Second, pagination is generally a function of the front-end and/or middleware, not the database layer.
But some database languages provide helpful facilities that aide in implementing pagination. For example, many SQL dialects provide LIMIT and OFFSET clauses that can be used to emit up to n rows starting at a given row number. I.e., a “page” of rows. If the query results are sorted via ORDER BY and are generally unchanged between successive invocations, then that can be used to implement pagination.
That may not be the most efficient or effective implementation, though.
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On context of web apps , let’s say there are 100 mn users. One cannot dump all the users in response.
Cache database query results in the middleware layer using Redis or similar and serve out pages of rows from that.
What if you have 30, 000 rows plus, do you fetch all of that from the database and cache in Redis?
I feel the most efficient solution is still offset and limit. It doesn’t make sense to use a database and then end up putting all of your data in Redis especially data that changes a lot. Redis is not for storing all of your data.
If you have large data set, you should use offset and limit, getting only what is needed from the database into main memory (and maybe caching those in Redis) at any point in time is very efficient.
With 30,000 rows in a table, if offset/limit is the only viable or appropriate restriction, then that’s sometimes the way to go.
More often, there’s a much better way of restricting 30,000 rows via some search criteria that significantly reduces the displayed volume of rows — ideally to a single page or a few pages (which are appropriate to cache in Redis.)
It’s unlikely (though it does happen) that users really want to casually browse 30,000 rows, page by page. More often, they want this one record, or these small number of records.
I know for MySQL there is LIMIT offset,size; and for Oracle there is ‘ROW_NUMBER’ or something like that.
But when such ‘paginated’ queries are called back to back, does the database engine actually do the entire ‘select’ all over again and then retrieve a different subset of results each time? Or does it do the overall fetching of results only once, keeps the results in memory or something, and then serves subsets of results from it for subsequent queries based on offset and size?
If it does the full fetch every time, then it seems quite inefficient.
If it does full fetch only once, it must be ‘storing’ the query somewhere somehow, so that the next time that query comes in, it knows that it has already fetched all the data and just needs to extract next page from it. In that case, how will the database engine handle multiple threads? Two threads executing the same query?
something will be quick or slow without taking measurements, and complicate the code in advance to download 12 pages at once and cache them because “it seems to me that it will be faster”.
Answer: First of all, do not make assumptions in advance whether something will be quick or slow without taking measurements, and complicate the code in advance to download 12 pages at once and cache them because “it seems to me that it will be faster”.
YAGNI principle – the programmer should not add functionality until deemed necessary. Do it in the simplest way (ordinary pagination of one page), measure how it works on production, if it is slow, then try a different method, if the speed is satisfactory, leave it as it is.
From my own practice – an application that retrieves data from a table containing about 80,000 records, the main table is joined with 4-5 additional lookup tables, the whole query is paginated, about 25-30 records per page, about 2500-3000 pages in total. Database is Oracle 12c, there are indexes on a few columns, queries are generated by Hibernate. Measurements on production system at the server side show that an average time (median – 50% percentile) of retrieving one page is about 300 ms. 95% percentile is less than 800 ms – this means that 95% of requests for retrieving a single page is less that 800ms, when we add a transfer time from the server to the user and a rendering time of about 0.5-1 seconds, the total time is less than 2 seconds. That’s enough, users are happy.
And some theory – see this answer to know what is purpose of Pagination pattern
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Link to Diagram - https://imgur.com/a/PEWQkMJ I am working on creating a database for a project I am doing for my friend. It will be used by a .NET Web API eventually. To try to keep it as simple as possible, I have left off fields that aren't related to the concerns. Project Overview Essentially the database is to store ticket purchases. There will be multiple purchases by the same purchaser across various seasons/leagues/teams. Each purchase could be for one game, or for all of the games. A purchase for a game could have different seats with different pricing for each combination of Section/Row/Seat. A purchase could also be for every game within a given season. If a purchase if for every game, it is likely they would have the same tickets for each game, but I do need to account for the possibility they wont. Things to keep in mind I have a Home Game table because I only care about the home games for the team the purchase is actually for. The League/Season/Team/HomeGame tables will all be synced automatically by an external API that will return the schedules for all teams in a given league. A Purchaser is stored in the DB and they can have multiple Phone Numbers/Emails/Addresses Home Game Table Questions I am worried about the redundancy of my relationships here. I currently have a reference to the League table here, which can be inferred by the Season Table or Team Table. Is the way I currently have it setup not the most ideal way to handle this? Purchase Table Questions When I actually query on this table I need to know how many games this purchase was for, which I am not sure if I can actually do that at the moment. I feel there is a ton of redundancy here but I am unsure how to avoid it. For example I am linking to all 4 of the Purchaser tables here which seems like a bit much. I am really open to any sort of feedback here, database design has always been a struggle of mine. Any tips or any sort of direction you believe I should go in, I am totally open to. submitted by /u/Nickt1596 [link] [comments]
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I’m trying to find a solution for work that would allow us to replace hand written QC forms with digital forms so the information can be more easily stored and accessed using a database. I’m sure this exists but I can’t seem to google the right combination of words to find it. Anyone seen an app like this before? submitted by /u/supermoto07 [link] [comments]
I'm working on an ecommerce website for my thesis project. Of course, that means I will also need a database for storing the products, orders, customers, etc. I decided to go with Postgres. I came up with this schema. Does this look okay? Are there any pitfalls I did not consider? I also stored the SQL for the creation of the tables here. If you guys have any tips for improvements I would love to hear that. Some parts that may be worth explaining: Order is called purchase since order is a reserved word in SQL Customer and address is one to many, since a customer can have more than one address. Every customer has only one default address, however. Shipping status in the purchase table shows a very short summary of the status, while the status updates store the exact events that happened to the purchase. Purchase and product table has the price in it due to the fact that the price of the product may change after the order, so we need to keep a copy of the original price A subcategory can only belong to one category submitted by /u/dont_mess_with_tx [link] [comments]
Hello folks, this is my setting: Azure SQL Server, a star Schema Table with a few metadata columns for indexing and one big varchar(max) column filled with a JSON Data. We run a typical data warehousing application, relatively few inserts, practically no updates, but many bulk reads. The table is approaching a million rows. I am overall very happy with functionality and performance, but I am constantly looking for things to improve. One bottleneck on very large bulk reads is I/O, which is quite expensive in Azure. Of course, the best way would be avoiding these, but I have no influence on that. I was reading into CCI and some of MS articles and documentation praise it for huge compression gains (which I don't care about) but also vast improvements of I/O performance, which I do care about. My understanding is the column is compressed in partitions, but how does that help I/O? Sure, less disk reads because the data is highly compressed, but in the end, if the client requests the data, it must be unpacked and delivered, so at some point the unpacked data must pass the I/O barrier, before it is compressed for transport again anyway. Also, if a query requests data from different partitions, doesn't that create a huge overhead for the DBMS? Is it worth a try? Am I on the wrong path? Does anybody have experience with a similar setting? submitted by /u/roboblocky [link] [comments]
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Hello Database community, We at Xinnor have been working on optimizing the performance of PostgreSQL databases, especially in virtual environments. We built a high-performance storage solution with Kioxia PCIe5 NVMe drives, motherboard by Supermicro and our RAID engine. I thought it might be of interest to this community. Have you tried any similar solutions? It would be great to learn more about your experience as well. More details in our blog post - https://xinnor.io/blog/high-performance-storage-solution-for-postgresql-database-in-virtual-environment-boosted-by-xiraid-engine-and-kioxia-pcie5-drives/ submitted by /u/PltnvS [link] [comments]
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Hello! Does anyone know articles regarding databases and schema comparison state-of-the-art? I am searching but haven't been able to find anything but the tools' features (e.g. Schema Compare from SSDT). I need some articles regarding the state-of-the-art of these tools. Thank you in advance submitted by /u/Wonderful_Self_2285 [link] [comments]
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