积分充值
 首页
前端开发
AngularDartElectronFlutterHTML/CSSJavaScriptReactSvelteTypeScriptVue.js构建工具
后端开发
.NetC#C++C语言DenoffmpegGoIdrisJavaJuliaKotlinLeanMakefilenimNode.jsPascalPHPPythonRISC-VRubyRustSwiftUML其它语言区块链开发测试微服务敏捷开发架构设计汇编语言
数据库
Apache DorisApache HBaseCassandraClickHouseFirebirdGreenplumMongoDBMySQLPieCloudDBPostgreSQLRedisSQLSQLiteTiDBVitess数据库中间件数据库工具数据库设计
系统运维
AndroidDevOpshttpdJenkinsLinuxPrometheusTraefikZabbix存储网络与安全
云计算&大数据
Apache APISIXApache FlinkApache KarafApache KyuubiApache OzonedaprDockerHadoopHarborIstioKubernetesOpenShiftPandasrancherRocketMQServerlessService MeshVirtualBoxVMWare云原生CNCF机器学习边缘计算
综合其他
BlenderGIMPKiCadKritaWeblate产品与服务人工智能亿图数据可视化版本控制笔试面试
文库资料
前端
AngularAnt DesignBabelBootstrapChart.jsCSS3EchartsElectronHighchartsHTML/CSSHTML5JavaScriptJerryScriptJestReactSassTypeScriptVue前端工具小程序
后端
.NETApacheC/C++C#CMakeCrystalDartDenoDjangoDubboErlangFastifyFlaskGinGoGoFrameGuzzleIrisJavaJuliaLispLLVMLuaMatplotlibMicronautnimNode.jsPerlPHPPythonQtRPCRubyRustR语言ScalaShellVlangwasmYewZephirZig算法
移动端
AndroidAPP工具FlutterFramework7HarmonyHippyIoniciOSkotlinNativeObject-CPWAReactSwiftuni-appWeex
数据库
ApacheArangoDBCassandraClickHouseCouchDBCrateDBDB2DocumentDBDorisDragonflyDBEdgeDBetcdFirebirdGaussDBGraphGreenPlumHStreamDBHugeGraphimmudbIndexedDBInfluxDBIoTDBKey-ValueKitDBLevelDBM3DBMatrixOneMilvusMongoDBMySQLNavicatNebulaNewSQLNoSQLOceanBaseOpenTSDBOracleOrientDBPostgreSQLPrestoDBQuestDBRedisRocksDBSequoiaDBServerSkytableSQLSQLiteTiDBTiKVTimescaleDBYugabyteDB关系型数据库数据库数据库ORM数据库中间件数据库工具时序数据库
云计算&大数据
ActiveMQAerakiAgentAlluxioAntreaApacheApache APISIXAPISIXBFEBitBookKeeperChaosChoerodonCiliumCloudStackConsulDaprDataEaseDC/OSDockerDrillDruidElasticJobElasticSearchEnvoyErdaFlinkFluentGrafanaHadoopHarborHelmHudiInLongKafkaKnativeKongKubeCubeKubeEdgeKubeflowKubeOperatorKubernetesKubeSphereKubeVelaKumaKylinLibcloudLinkerdLonghornMeiliSearchMeshNacosNATSOKDOpenOpenEBSOpenKruiseOpenPitrixOpenSearchOpenStackOpenTracingOzonePaddlePaddlePolicyPulsarPyTorchRainbondRancherRediSearchScikit-learnServerlessShardingSphereShenYuSparkStormSupersetXuperChainZadig云原生CNCF人工智能区块链数据挖掘机器学习深度学习算法工程边缘计算
UI&美工&设计
BlenderKritaSketchUI设计
网络&系统&运维
AnsibleApacheAWKCeleryCephCI/CDCurveDevOpsGoCDHAProxyIstioJenkinsJumpServerLinuxMacNginxOpenRestyPrometheusServertraefikTrafficUnixWindowsZabbixZipkin安全防护系统内核网络运维监控
综合其它
文章资讯
 上传文档  发布文章  登录账户
IT文库
  • 综合
  • 文档
  • 文章

无数据

分类

全部后端开发(1290)Python(452)Java(367)综合其他(331)Spring(314)云计算&大数据(275)Weblate(212)数据库(186)C++(159)VirtualBox(113)

语言

全部英语(2173)

格式

全部PDF文档 PDF(1589)其他文档 其他(509)TXT文档 TXT(68)PPT文档 PPT(4)DOC文档 DOC(3)
 
本次搜索耗时 0.063 秒,为您找到相关结果约 1000 个.
  • 全部
  • 后端开发
  • Python
  • Java
  • 综合其他
  • Spring
  • 云计算&大数据
  • Weblate
  • 数据库
  • C++
  • VirtualBox
  • 全部
  • 英语
  • 全部
  • PDF文档 PDF
  • 其他文档 其他
  • TXT文档 TXT
  • PPT文档 PPT
  • DOC文档 DOC
  • 默认排序
  • 最新排序
  • 页数排序
  • 大小排序
  • 全部时间
  • 最近一天
  • 最近一周
  • 最近一个月
  • 最近三个月
  • 最近半年
  • 最近一年
  • pdf文档 GNU Image Manipulation Program User Manual 2.4

    GNU Image Manipulation Program 1 / 653 GNU Image Manipulation Program User Manual GNU Image Manipulation Program 2 / 653 Copyright © 2002, 2003, 2004, 2005, 2006, 2007 The GIMP Documentation Team the section enphrased GNU Free Documentation License. GNU Image Manipulation Program 3 / 653 COLLABORATORS TITLE : REFERENCE : GNU Image Manipulation Program ACTION NAME DATE SIGNATURE WRITTEN BY 2007 REVISION HISTORY NUMBER DATE DESCRIPTION NAME $Revision: 1985 $ 2007-07-15 romanofski GNU Image Manipulation Program 4 / 653 Contents I Getting started 21 1 Introduction 22 1.1 Welcome to the
    0 码力 | 653 页 | 19.93 MB | 1 年前
    3
  • pdf文档 GNU Image Manipulation Program User Manual 2.10

    GNU Image Manipulation Program User Manual November 17, 2021 GNU Image Manipulation Program Copyright © 2002-2021 The GIMP Documentation Team Legal Notice Permission is granted to copy, distribute Toolbox . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.2.2 Image Window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2.3 Dialogs . . . . . . . . 26 3.4.2 Change the Size of an Image for the screen . . . . . . . . . . . . . . . . . . . . . . . 26 3.4.3 Change the Size of an Image for print . . . . . . . . . . . . . . . . . . .
    0 码力 | 1070 页 | 44.54 MB | 1 年前
    3
  • pdf文档 Stream processing fundamentals - CS 591 K1: Data Stream Processing and Analytics Spring 2020

    Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 1/23: Stream Processing Fundamentals Vasiliki Kalavri | Boston University University 2020 What is a stream? • In traditional data processing applications, we know the entire dataset in advance, e.g. tables stored in a database. A data stream is a data set that is produced incrementally incrementally over time, rather than being available in full before its processing begins. • Data streams are high-volume, real-time data that might be unbounded • we cannot store the entire stream
    0 码力 | 45 页 | 1.22 MB | 1 年前
    3
  • pdf文档 2.1.5 Processing XML and Spreadsheet Data in Go

    Processing XML and Spreadsheet in Go 续 日 Gopher China Conference Beijing 2021 6/26 - 6/27 Self Introduction The author of the Excelize - Go language spreadsheet library. Familiar with Go language Complex XML 02 • Partial Load • Namespace & Entity • Ser/Deserialize Idempotence High Performance Processing 03 • XML Schema Definition • DOM or SAX OOXML Spreadsheets 04 • Excel XML Specification • work:addr="WORK"> High Performance Processing XML Components Data Model Tom
    0 码力 | 35 页 | 1.34 MB | 1 年前
    3
  • pdf文档 Scalable Stream Processing - Spark Streaming and Flink

    Scalable Stream Processing - Spark Streaming and Flink Amir H. Payberah payberah@kth.se 05/10/2018 The Course Web Page https://id2221kth.github.io 1 / 79 Where Are We? 2 / 79 Stream Processing Systems Design Design Issues ▶ Continuous vs. micro-batch processing ▶ Record-at-a-Time vs. declarative APIs 3 / 79 Outline ▶ Spark streaming ▶ Flink 4 / 79 Spark Streaming 5 / 79 Contribution ▶ Design issues issues • Continuous vs. micro-batch processing • Record-at-a-Time vs. declarative APIs 6 / 79 Spark Streaming ▶ Run a streaming computation as a series of very small, deterministic batch jobs. • Chops
    0 码力 | 113 页 | 1.22 MB | 1 年前
    3
  • pdf文档 【04 RocketMQ 王鑫】Stream Processing with Apache RocketMQ and Apache Flink

    0 码力 | 30 页 | 24.22 MB | 1 年前
    3
  • pdf文档 Skew mitigation - CS 591 K1: Data Stream Processing and Analytics Spring 2020

    ??? Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 4/16: Skew mitigation ??? Vasiliki Kalavri | Uddin Nasir et. al. The power of both choices: Practical load balancing for distributed stream processing engines. ICDE 2015. • Mitzenmacher, Michael. The power of two choices in randomized load balancing
    0 码力 | 31 页 | 1.47 MB | 1 年前
    3
  • pdf文档 State management - CS 591 K1: Data Stream Processing and Analytics Spring 2020

    Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 2/25: State Management Vasiliki Kalavri | Boston operator. Keyed state can only be used by functions that are applied on a KeyedStream: • When the processing method of a function with keyed input is called, Flink’s runtime automatically puts all keyed fare, Collector> out) throws Exception {
 // similar logic for processing fare events
 }
 }
 } Java example (cont.) 21 Vasiliki Kalavri | Boston University 2020
    0 码力 | 24 页 | 914.13 KB | 1 年前
    3
  • pdf文档 Streaming optimizations - CS 591 K1: Data Stream Processing and Analytics Spring 2020

    Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 4/14: Stream processing optimizations ??? Vasiliki Kalavri | Boston University serialization cost • if operators are separate, throughput is bounded by either communication or processing cost • if fused, throughput is determined by operator cost only Operator fusion A B A B is statically configured with a certain number of processing slots that defines the maximum number of concurrent tasks it can execute. • A processing slot can execute one slice of an application, i.e
    0 码力 | 54 页 | 2.83 MB | 1 年前
    3
  • pdf文档 Windows and triggers - CS 591 K1: Data Stream Processing and Analytics Spring 2020

    Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 2/11: Windows and Triggers Vasiliki Kalavri | Boston windowing use cases: • They assign an element based on its event-time timestamp or the current processing time to windows. • Time windows have a start and an end timestamp. • All built-in window assigners assigners provide a default trigger that triggers the evaluation of a window once the (processing or event) time passes the end of the window. • A window is created when the first element is assigned
    0 码力 | 35 页 | 444.84 KB | 1 年前
    3
共 1000 条
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 100
前往
页
相关搜索词
GNUImageManipulationProgramUserManual2.42.10StreamprocessingfundamentalsCS591K1DataProcessingandAnalyticsSpring20202.1XMLSpreadsheetinGoScalableSparkStreamingFlink04RocketMQ王鑫withApacheSkewmitigationStatemanagementoptimizationsWindowstriggers
IT文库
关于我们 文库协议 联系我们 意见反馈 免责声明
本站文档数据由用户上传或本站整理自互联网,不以营利为目的,供所有人免费下载和学习使用。如侵犯您的权益,请联系我们进行删除。
IT文库 ©1024 - 2025 | 站点地图
Powered By MOREDOC AI v3.3.0-beta.70
  • 关注我们的公众号【刻舟求荐】,给您不一样的精彩
    关注我们的公众号【刻舟求荐】,给您不一样的精彩