caching

问题 I am currently caching dynamically generated PHP pages by saving them to a database with an expiry time field. If the page is requested again, the program checks for a unexpired cached version of the page to serve up, and only regenerates the page if it can't find one. This works well - but would it put less load on the server to save the cached pages as files instead saving to the database? I could use a naming convention in the files to handle the expiry time. If it is faster and less

问题 According to these micro benchmarks it turns out that Caffeine is a way faster than Guava cache in both read and write operations. What is the secret of Caffeine implementation? How it differs from the Guava Cache? Am I right that in case of timed expiration Caffeine use a scheduled executor to perform appropriate maintenance operations in background? 回答1: The main difference is because Caffeine uses ring buffers to record & replay events, whereas Guava uses ConcurrentLinkedQueue . The intent

问题 How is the behavior of memory_only and memory_and_disk caching level in spark differ? 回答1: Documentation says --- Storage Level Meaning MEMORY_ONLY Store RDD as deserialized Java objects in the JVM. If the RDD does not fit in memory, some partitions will not be cached and will be recomputed on the fly each time they're needed. This is the default level. MEMORY_AND_DISK Store RDD as deserialized Java objects in the JVM. If the RDD does not fit in memory, store the partitions that don't fit on

问题 How is the behavior of memory_only and memory_and_disk caching level in spark differ? 回答1: Documentation says --- Storage Level Meaning MEMORY_ONLY Store RDD as deserialized Java objects in the JVM. If the RDD does not fit in memory, some partitions will not be cached and will be recomputed on the fly each time they're needed. This is the default level. MEMORY_AND_DISK Store RDD as deserialized Java objects in the JVM. If the RDD does not fit in memory, store the partitions that don't fit on

问题 docker build is not using it's cache. docker build -f Dockerfile . generates the same output that this does: docker build -f Dockerfile --no-cache . I am modifying the Dockerfile, adding commands at the end of the file. So the previous layers should be cached and valid. I've got plenty of disk space. Any ideas? Docker version 17.06.1-ce, build 874a737 Dockerfile: FROM registry:5000/base/python:xenial RUN mkdir /code COPY . /code RUN apt-get update && \ apt-get install -y \ vim \ less COPY

问题 Least Frequently Used (LFU) is a type of cache algorithm used to manage memory within a computer. The standard characteristics of this method involve the system keeping track of the number of times a block is referenced in memory. When the cache is full and requires more room the system will purge the item with the lowest reference frequency. What would be the best way to implement a most-recently-used cache of objects, say in Java? I've already implemented one using LinkedHashMap(by

问题 I know that Blade already caches the compiled PHP for all blade views, but I would like to take this a step further. A website that I'm working on is modularized into component views and then pieced together in the default controller. Each of the "widgets" has its own view, which rarely changes content (with the exception of a few frequently updating ones). So, I'd like to cache the HTML output of these rarely-changing views to prevent them from being evaluated on every page load. In Laravel

问题 What's the difference between displaying a SVG image in an <img> or <object> tag? I was facing some problems using SVG images in a <img> tag on Android 3.1: The shape in the upper example is an <img> tag and the lowest example is the exact same image but display in an <object> . Why is this displayed a different way? And is an <object> cached like an <img> ? What do you guys suggest? 回答1: Differences when SVG is used as an image (html <img> SVG <image> or CSS background images) no scripting

问题 The Apache Spark SQL operation CACHE table has an option so that it runs lazy. But what about UNCACHE table ? The documentation doesn't say anything if it is lazy or not. Will the table be dropped immediately from cache or will it be deferred until the next run of the garbage collection? If it is lazy, is there a way to find out, if my table is still cached or not? 回答1: The default UNCACHE operation is non-blocking. If you use the DSL, you can call df.unpersist(true) on a dataframe/dataset to

问题 I created a new c# project and follwed the steps from this tutorial to create a LocalDataCache: http://www.codeproject.com/KB/database/AdoSyncServicesArticalPKg.aspx?fid=1526739&df=90&mpp=25&noise=3&sort=Position&view=Quick&select=2794305&fr=1#xx0xx I next added the following code: using System; using System.Collections.Generic; using System.ComponentModel; using System.Data; using System.Drawing; using System.Linq; using System.Text; using System.Windows.Forms; namespace TestLocalSync {