pyflink-docs Release release-1.15 PyFlink Nov 23, 2022 CONTENTS 1 How to build docs locally 3 1.1 Getting Started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 i ii pyflink-docs, Release release-1.15 PyFlink is a Python API for Apache Flink that allows you to build scalable batch and streaming workloads PyFlink: PyFlink Table API and PyFlink DataStream API. CONTENTS 1 pyflink-docs, Release release-1.15 2 CONTENTS CHAPTER ONE HOW TO BUILD DOCS LOCALLY 1. Install dependency requirements python3

com/conan-io/conan for issues and more details about development, contributors, etc. Important: Conan 1.15 shouldn’t break any existing 1.0 recipe or command line invocation. If it does, please submit a report

一行代码造成大量消息丢失 115 1.13 RocketMQ DLedger 多副本即主从切换实战 121 1.14 RocketMQ msgId 与 offsetMsgId 释疑 131 1.15 RocketMQ ACL 使用指南 141 1.16 RocketMQ 消息轨迹-设计篇 151 1.17 消息发送常见问题与解决方案 155 本文来自『中间件兴趣圈』公众号，仅作技术交流，未授权任何商业行为。 快速定位到该条消息。 rocketmq-console 消息查找消息列表中的 id 又是什么呢？ 本文来自『中间件兴趣圈』公众号，仅作技术交流，未授权任何商业行为。 141 > 1.15 RocketMQ ACL 使用指南 1.15 RocketMQ ACL 使用指南 一、什么是 ACL? ACL 是 access control list 的简称，俗称访问控制列表。访问控制，基本上会涉及 到用户、资源、权限、角色等概念，那在 进行白名单设置。 二、ACL 基本流程图 在讲解如何使用 ACL 之前，我们先简单看一下 RocketMQ ACL 的请求流程： 本文来自『中间件兴趣圈』公众号，仅作技术交流，未授权任何商业行为。 1.15 RocketMQ ACL 使用指南 < 142 对于上述具体的实现，将在后续文章中重点讲解，本文的目的只是希望给读者一个大概 的了解。 三、如何配置 ACL 1. acl 配置文件 acl

Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 1.15 SQLite Extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . callback to be executed when the proxy is initialized. 1.15 SQLite Extensions The default SqliteDatabase already includes many SQLite-specific features: 1.15. SQLite Extensions 179 peewee Documentation, Release of query, either INSERT, UPDATE or DELETE. • database name - the default database is named main. 1.15. SQLite Extensions 181 peewee Documentation, Release 3.4.0 • table name - name of table being modified

Version Supported PyFlink Version Python Version Supported PyFlink 1.16 Python 3.6 to 3.9 PyFlink 1.15 Python 3.6 to 3.8 PyFlink 1.14 Python 3.6 to 3.8 You could check your Python version as following: version and PyFlink version need to be consistent. For example, if you are using Flink 1.15, then you should use PyFlink 1.15 Installing using PyPI PyFlink could be installed using PyPI as following: python3 zip/venv/bin/python3 \ -py shipfiles/word_count.py Note: Per-Job mode has been deprecated since Flink 1.15 and may be dropped in the future releases. It’s suggested to use Application mode. See YARN Per-Job

Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 1.15 SQLite Extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . parameter, the bound object. Returns self Add a callback to be executed when the proxy is initialized. 1.15 SQLite Extensions The default SqliteDatabase already includes many SQLite-specific features: • General support, for efficient binary data storage. • Additional helpers, including bloom filter, more. 1.15. SQLite Extensions 177 peewee Documentation, Release 3.3.0 1.15.1 Getting started To get started

Kubernetes cluster. The DaemonSet will automa�cally install itself as Kubernetes CNI plugin. K8s 1.15 K8s 1.14 K8s 1.13 K8s 1.12 K8s 1.11 K8s 1.10 kubectl create -f https://raw.githubusercontent Kubernetes cluster. The DaemonSet will automa�cally install itself as Kubernetes CNI plugin. K8s 1.15 K8s 1.14 K8s 1.13 K8s 1.12 K8s 1.11 K8s 1.10 kubectl create -f https://raw.githubusercontent pods to communicate during the bootstrapping phase of Cilium. For Docker as container runtime: K8s 1.15 K8s 1.14 K8s 1.13 K8s 1.12 K8s 1.11 K8s 1.10 kubectl apply -f https://raw.githubusercontent

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 1.15 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . held in memory. You can manage the amount of tasks in a clusters memory by setting the queue_limit. 1.15 Examples 1.15.1 Emails Sending an email can take a while so why not queue it: # Welcome mail with tasks import async_task, schedule from django_q.models import Schedule (continues on next page) 1.15. Examples 47 Django Q Documentation, Release 1.3.6 (continued from previous page) def welcome_mail(user):

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 1.15 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . held in memory. You can manage the amount of tasks in a clusters memory by setting the queue_limit. 1.15 Examples 1.15.1 Emails Sending an email can take a while so why not queue it: # Welcome mail with in other objects too. Let’s say this users email address is not just on the User object, but you 1.15. Examples 49 Django Q Documentation, Release 1.3.6 stored it in some other places too without a

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 1.15 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . held in memory. You can manage the amount of tasks in a clusters memory by setting the queue_limit. 1.15 Examples 1.15.1 Emails Sending an email can take a while so why not queue it: # Welcome mail with right away async('django.core.mail.send_mail', 'Welcome', msg, 'from@example.com', [user.email]) 1.15. Examples 45 Django Q Documentation, Release 0.9.0 # and this follow up email in one hour msg =