query-cache | Easily Cache Eloquent Collections | Database library
kandi X-RAY | query-cache Summary
kandi X-RAY | query-cache Summary
This Laravel 5 package allows you to easily cache eloquent queries by implementing laravel 4 remember method. ##How to use ###Step 1: Install Through Composer. ###Step 2: Use QueryCache In Your Model. ###Step 3: Use remember Method When Quering Eloquent When calling remember method you can tell it for how many minutes you want the query be cached. If you dont specify the minutes, the query will be cached for 60 minutes. ##More Features ###Global Cache If you want you can cache all queries for a specific model by siply defining cacheAll var inside your model. QueryCache will aply remember method to all model queries. ###Clear Cache On Change If you want the cache to be flushed when you create, delete, or update an existing model then define $clearOnChange. ###Cache Tags QueryCache will use the model name as cache tags. You can also define custon cache tags.
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Top functions reviewed by kandi - BETA
- Get the cached result .
- Boot the query cache .
- Set cache tags .
- Get cache tags .
- Get cache callback .
- Create a new QueryBuilder
- Clear cache .
- Applies the cache to the builder .
- Remove the given model from the given builder .
- Return a new query without caching context .
query-cache Key Features
query-cache Examples and Code Snippets
Lines of Code : 42
License : No License
Copycomposer require kyrenator/query-cache
\App\Post::remember()->take(3)->get();
//use cache tags
\App\Post::remember()->cacheTags('posts', 'fresh')->take(3)->get();
Community Discussions
Trending Discussions on query-cache
QUESTION
I have never used apc_store() before, and I'm also not sure about whether to free query results or not. So I have these questions...
In a MySQL Query Cache article here, it says "The MySQL query cache is a global one shared among the sessions. It caches the select query along with the result set, which enables the identical selects to execute faster as the data fetches from the in memory."
Does using free_result() after a select query negate the caching spoken of above?
Also, if I want to set variables and arrays obtained from the select query for use across pages, should I save the variables in memory via apc_store() for example? (I know that can save arrays too.) And if I do that, does it matter if I free the result of the query? Right now, I am setting these variables and arrays in an included file on most pages, since they are used often. This doesn't seem very efficient, which is why I'm looking for an alternative.
Thanks for any help/advice on the most efficient way to do the above.
...ANSWER
Answered 2021-May-21 at 16:47MySQL's "Query cache" is internal to MySQL. You still have to perform the SELECT; the result may come back faster if the QC is enabled and usable in the situation.
I don't think the QC is what you are looking for.
The QC is going away in newer versions. Do not plan to use it.
In PHP, consider $_SESSION. I don't know whether it is better than apc_store for your use.
Note also, anything that is directly available in PHP constrains you to a single webserver. (This is fine for small to medium apps, but is not viable for very active apps.)
For scaling, consider storing a small key in a cookie, then looking up that key in a table in the database. This provides for storing arbitrary amounts of data in the database with only a few milliseconds of overhead. The "key" might be something as simple as a "user id" or "session number" or "cart number", etc.
QUESTION
Does SQLite have any notion of a query cache? For example, if I execute the same query two times in a row:
...ANSWER
Answered 2019-Sep-23 at 19:29AFAIK SQLite does not have a built-in query cache. You'd have to add one at the application layer, probably by using an ORM which provides a query cache.
What it does do is cache database pages in memory for faster retrieval. You can adjust the size of this cache with the cache_size pragma. By default it is 2000 kibibytes (2 megs). Try something larger. For example, 20,000 kb (20 megs).
QUESTION
Apparently, when using the BigQuery API, there is a cacheHit property of a BigQuery result. I've tried finding this property and I'm not sure how I need to access it. Here's my Java code that uses the BigQuery API. cacheHit isn't a property of the TableResult tr that I get:
ANSWER
Answered 2019-Jul-22 at 23:34QueryStatistics is one of the nested classes of JobStatistics as can be seen here and has a getCacheHit() method:
QUESTION
I configured Hazelcast as L2C for Hibernate. Then made 1st request using hibernate query builder with query cache hint and I got:
...ANSWER
Answered 2019-Feb-01 at 08:06Hibernate does not store query result in the 'query' region as a whole; it rather stores set of ids, where the entities are in other 'entity' regions.
My guess: If something is misconfigured and Hazelcast does not store the entities themselves, it's possible that while the list of entry ids is known from the query cache, it loads the actual entities one-by-one.
Do the query and check sizes of cache regions.
QUESTION
I have a strange problem.
On MySQL 5.6 I have query cache enabled, with the below settings.
The idea of caching is that whenever a write operation happens, the record is invalidated (removed) and created upon next read.
However, I do get the stale data a lot of the times, and it gets corrected when I change some characters in the query.
I know turning off query cache is certainly an option that works, but am I doing something wrong here in terms of settings related to query cache?
I read about write-through caching, but couldn't find any default implementation of it in MySQL nor does it mention anywhere about the invalidations clearly.
Another important point is - I do have a lot of connection objects live at any point of time (a few tens), is it possible that my issue is because of some caching at connection level (if possible) instead of global cache?
EDIT - NOT a duplicate question to
What is the use of "query_cache_wlock_invalidate" in MySql Query Cache?
because here the issue is that the cached value is being returned even after a long time after the write happened, as expectation is that the write resulted in cache invalidation anyways as the lock would have also been given up by then.
EDIT -
query_cache_wlock_invalidate actually worked. The issue was with incorrect logging of write timestamp which resulted in invalid conclusion.
ANSWER
Answered 2018-Aug-08 at 04:57Setting query_cache_wlock_invalidate to ON works.
QUESTION
I have a server with 2 CPU cores and 1GB of RAM.The server only run one wordpress site.My Server Stack is LEMP.I ran mysql tuner two weeks after setting up the wordpress site. Here are the results
...ANSWER
Answered 2018-Jul-25 at 08:10There is one terribly bad setting:
QUESTION
I want to use entityframework-plus extension to cache some of my queries, but it does not have any option to select specific items and cache them, as I read its document, it caches all of the columns like this :
...ANSWER
Answered 2018-Jun-27 at 10:43FromCache() method can only be used on IQueryable objects. As your .Select(x => x.tbl_ProductID) instruction returns an IQueryable (or whatever type tbl_ProductID is) you won't be able to use the extension method.
You can download the whole source code from GitHub and see the class file CacheExtensions.cs
QUESTION
I'm using the elasticsearch version 6.1.1. I've been running queries in the filter context on an index on which I've explicitly enabled query cache. But the query cache is empty. I found a similar case on the elasticsearch discuss forums (https://discuss.elastic.co/t/query-cache-is-empty/84515 ), but it doesn't have a solution listed. As per the documentation here, https://www.elastic.co/guide/en/elasticsearch/reference/current/query-cache.html, the query cache should work for queries run in the filter context.
After I succsefully run this,
...ANSWER
Answered 2018-Jan-31 at 10:25There is a bug in 6.x of term filter, it can't be query cached. see:
https://github.com/elastic/elasticsearch/pull/27190
so maybe you can try range filter or exists for query cache. and also your docs need to big enough(I test in 100k documents) for query cache.
QUESTION
New to Amazon RDS, I'm looking for ways to deliver cached SELECT queries to enhance performance of a query heavy website (along with other features leading to interest in RDS). So far I've been able to setup an Amazon Aurora database, migrate an old MySQL database to it via MySQLWorkbench and run a test version of the website successfully. The website is connecting to Aurora remotely, running outside of AWS.
I was reading that I could increase the MySQL Query Cache using queries, e.g. (16MB in this case):
...ANSWER
Answered 2018-Jan-11 at 04:53On an RDS instance, you will generally manage engine configuration like this through RDS parameter groups.
AWS publishes a list of parameters that are available in Aurora MySQL parameter groups, and it appears that query_cache_size is modifiable as an instance-level parameter.
There are some differences between Aurora cluster and instance level parameter groups that you should be aware of. Per the linked documentation above:
Further ReadingCluster-level parameters are managed in DB cluster parameter groups. Instance-level parameters are managed in DB parameter groups. Although each DB instance in an Aurora MySQL DB cluster is compatible with the MySQL database engine, some of the MySQL database engine parameters must be applied at the cluster level, and are managed using DB cluster parameter groups. Cluster-level parameters are not found in the DB parameter group for an instance in an Aurora DB cluster and are listed later in this topic.
You can manage both cluster-level and instance-level parameters using the AWS Management Console, the AWS CLI, or the Amazon RDS API. There are separate commands for managing cluster-level parameters and instance-level parameters. For example, you can use the modify-db-cluster-parameter-group AWS CLI command to manage cluster-level parameters in a DB cluster parameter group and use the modify-db-parameter-group AWS CLI command to manage instance-level parameters in a DB parameter group for a DB instance in a DB cluster.
QUESTION
I am attempting to make a query run on a large database in acceptable time. I'm looking at optimizing the query itself (e.g. Clarification of join order for creation of temporary tables), which took me from not being able to complete the query at all (with a 20 hr cap) to completing it but with time that's still not acceptable.
In experimenting, I found the following strange behavior that I'd like to understand: I want to do the query over a time range of 2 years. If I try to run it like that directly, then it still will not complete within the 10 min I'm allowing for the test. If I reduce it to the first 6 months of the range, it will complete pretty quickly. If I then incrementally re-run the query by adding a couple of months to the range (i.e. run it for 8 months, then 10 months, up to the full 2 yrs), each successive attempt will complete and I can bootstrap my way up to being able to get the full two years that I want.
I suspected that this might be possible due to caching of results by the MySQL server, but that does not seem to match the documentation:
If an identical statement is received later, the server retrieves the results from the query cache rather than parsing and executing the statement again.
http://dev.mysql.com/doc/refman/5.7/en/query-cache.html
The key word there seems to be "identical," and the apparent requirement that the queries be identical was reenforced by other reading that I did. (The docs even indicate that the comparison on the query is literal to the point that logically equivalent queries written with "SELECT" vs. "select" would not match.) In my case, each subsequent query contains the full range of the previous query, but no two of them are identical.
Additionally, the tables are updated overnight. So at the end of the day yesterday we had the full, 2-yr query running in 19 sec when, presumably, it was cached since we had by that point obtained the full result at least once. Today we cannot make the query run anymore, which would seem to be consistent with the cache having been invalidated when the table was updated last night.
So the questions: Is there some special case that allows the server to cache in this case? If yes, where is that documented? If not, any suggestion on what else would lead to this behavior?
...ANSWER
Answered 2017-Jan-21 at 09:49Yes, there is a cache that optimizes (general) access to the harddrive. It is actually a very important part of every storage based database system, because reading data from (or writing e.g. temporary data to) the harddrive is usually the most relevant bottleneck for most queries.
For InnoDB, this is called the InnoDB Buffer Pool:
InnoDB maintains a storage area called the buffer pool for caching data and indexes in memory. Knowing how the InnoDB buffer pool works, and taking advantage of it to keep frequently accessed data in memory, is an important aspect of MySQL tuning. For information about how the InnoDB buffer pool works, see InnoDB Buffer Pool LRU Algorithm.
You can configure the various aspects of the InnoDB buffer pool to improve performance.
- Ideally, you set the size of the buffer pool to as large a value as practical, leaving enough memory for other processes on the server to run without excessive paging. The larger the buffer pool, the more InnoDB acts like an in-memory database, reading data from disk once and then accessing the data from memory during subsequent reads. See Section 15.6.3.2, “Configuring InnoDB Buffer Pool Size”.
There can be (and have been) written books about the buffer pool, how it works and how to optimize it, so I will stop there and just leave you with this keyword and refer you to the documentation.
Basically, your subsequent reads add data to the cache that can be reused until it has been replaced by other data (which in your case has happened the next day). Since (for MySQL) this can be any read of the involved tables and doesn't have to be your maybe complicated query, it might make the "prefetching" easier for you.
Although the following comes with a disclaimer because it obviously can have a negative impact on your server if you change your configuration: the default MySQL configuration is very (very) conservative, and e.g. the innodb_buffer_pool_size system setting is way too low for most servers younger than 15 years, so maybe have a look at your configuration (or let your system administrator check it).
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Install query-cache
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