Delta | 易学教程

Limit while loop to run at 30 “FPS” using a delta variable C++

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问题 I basically need a while loop to only run at 30 "FPS". I was told to do this: "Inside your while loop, make a deltaT , and if that deltaT is lesser than 33 miliseconds use sleep(33-deltaT) ." But I really wasn't quite sure how to initialize the delta/what to set this variable to. I also couldn't get a reply back from the person that suggested this. I'm also not sure why the value in sleep is 33 instead of 30. Does anyone know what I can do about this? This is mainly for a game server to

GDIFF and BSDIFF algorithm needed

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问题 i could not find the working algorithm of the above two ,so can anyone provide me on how GDIFF and BSDIFF works? 来源： https://stackoverflow.com/questions/29184826/gdiff-and-bsdiff-algorithm-needed

Obtaining momentum quaternion from two quaternions and timestep

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问题 I have a quaternion which holds the rotation of an object. During the frame I modify it and obtain a new quaternion. I can calculate a quaternion that rotates from 'previous frame' to 'current frame'. I cannot figure out, however, how to 'divide by t' this quaternion to get the rotation-per-second that I need. I.e, based on the timestep, I need to know what the quaternion would look like had it been applied to itself an X amount of times (meaning, 28.5 times at 28.5 fps, etcetera). Would

Inexplicable SVN repository size increase from small differences to big files

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问题 I can't figure out why small differences to big files are causing my subversion repository to grow so much. I have a zip file of the contents a database used by some tests. I want to store each new version of the test data in our subversion repository. I've done some experiments, checking in the last few versions of the data.zip and looking at what happens to the size of the repository. The uncompressed data is about 150MB, compressed and zipped it's ~50MB. Each new version of the data.zip

Update data only by difference between files (delta for java)

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问题 UPDATE: I solved the problem with a great external library - https://code.google.com/p/xdeltaencoder/. The way I did it is posted below as the accepted answer Imagine I have two separate pcs who both have an identical byte[] A. One of the pcs creates byte[] B, which is almost identical to byte[] A but is a 'newer' version. For the second pc to update his copy of byte[] A into the latest version (byte[] B), I need to transmit the whole byte[] B to the second pc. If byte[] B is many GB's in

Is there a way to update SQLITE database using deltas?

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问题 I would like to know if SQLite proposes a update mechanism based on some delta file, to be clear for example an Oracle database can be synchronized with sql redo logs or snapshot logs. Does SQLite proposes an optimized mechanism to update itself. My use case is the following, I have a local database which must be synchronized with some remote data, in ideal world I would like to build in an optimized format the changes and only them, not all the database, is there some native SQLite mechanism

Bubbling scroll/mousewheel event

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问题 I've setup my app/website such that I have an absolute-positioned canvas element on top of a scrollpanel, when the scrollpanel scrolls I apply on offset to the canvas to make it look like the image is scrolling (this allows me to have huge canvas without the overhead of a huge canvas element). The problem is, when my mouse is over the canvas element, the scroll wheel does not work, since the scroll event does not bubble. In this case, however, I need the bubbling to get the scrollbar to work.

基于MaxCompute InformationSchema进行冷门表热门表访问分析

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一、需求场景分析在实际的数据平台运营管理过程中，数据表的规模往往随着更多业务数据的接入以及数据应用的建设而逐渐增长到非常大的规模，数据管理人员往往希望能够利用元数据的分析来更好地掌握不同数据表的使用情况，从而优化数据模型。一个MaxCompute项目中经常使用的表简称为热门表，使用次数较少或者很长时间不使用的表简称为冷门表，本文将介绍如何去通过MaxCompute元数据信息去分析热门表和冷门表。二、方案设计思路 MaxCompute Information_Schema提供了项目中全量的表元数据信息Tables以及包含访问表的作业明细数据tasks_history，通过汇总各个表被作业访问的次数可以获知不同表被作业使用的频度。详细步骤如下： 1、热门数据通过获取tasks_history表里的input_tables字段的详细信息，然后通过count统计一定时间分区内的各个表使用次数 2、冷门数据通过tables和tasks_history里的input_tables表的作业汇总数量进行关联、排序，从而统计出各张表在规定时间内的使用次数，正序排列三、方案实现方法 1、获取tasks_history表里的input_tables字段的详细信息。如下图所示：查询数据的结果如下图所示：发现在tasks_history表中input_tables字段格式为 [

Facebook：对比COPA 与CUBIC，BBR v1在拥塞控制及视频质量的表现

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Facebook的测试结果显示，COPA较于常用算法CUBIC及BBR v1存在一定优势，来看看具体表现。文 / Nitin Garg 译 / Adrian Ng 原文 https://engineering.fb.com/video-engineering/copa/ 在对互联网应用进行性能优化时，可能会涉及一些复杂的权衡。在传输大量数据的时候，如果传输速度过快，可能会因为丢包而产生重传，从而随着时间流逝导致性能损失。同时，如果发送数据的速度太慢则可能会导致延迟和卡顿，对性能也有很大的损害。此外，不同的视频体验需要针对质量与延迟进行不同的权衡。对于交互式体验，其应用程序可通过降低视频质量，避免卡顿。但当视频的高质量是最重要的因素时，应用程序可以在合理的范围内的保持一定延迟。此时，应用通常会在几种不同的拥塞控制算法中进行选择，找到最适合当前目标的优化算法进行优化。尽管在拥塞控制领域上我们已进行了广泛的研究，但若要将研究付诸实践一直以来都会涉及到修改Linux内核。使用QUIC可以在无需修改内核的情况下，在用户空间中实现整个传输堆栈，简化整个部署和实验的流程。而COPA 与 QUIC 的耦合可以为我们提供一种算法，该算法可适用于各种视频体验，并且可以合理地遵循一种部署策略。在实际测试中，测试结果显示COPA较于常用算法CUBIC及BBR v1存在一定优势

是时候改变你数仓的增量同步方案了

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经过一段时间的演化，spark-binlog，delta-plus慢慢进入正轨。spark-binlog可以将MySQL binlog作为标准的Spark数据源来使用，目前支持insert/update/delete 三种事件的捕捉。 delta-plus则是对Delta Lake的一个增强库，譬如在Delta Plus里实现了将binlog replay进Detla表，从而保证Delta表和数据库表接近实时同步。除此之外，detla-plus还集成了譬如布隆过滤器等来尽快数据更新更新速度。更多特性可参考我写的专栏。数据湖Delta Lake 深入解析 zhuanlan.zhihu.com 图标有了这两个库，加上Spark,我们就能通过两行代码完成库表的同步。以前如果要做数据增量同步，大概需要这么个流程：问题很明显，Pipeline长，涉及到技术多，中间转存其实也挺麻烦的，难做到实时。我们希望可以更简单些，比如最好是这样：然后我可能只要写如下代码就可以搞定： val spark: SparkSession = ??? val df = spark.readStream. format("org.apache.spark.sql.mlsql.sources.MLSQLBinLogDataSource"). option("host","127.0.0.1").

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