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new 22b8d419f1 [INLONG-801][Doc] Add blog for the 1.8.0 release (#814)
22b8d419f1 is described below
commit 22b8d419f11cea0bdcfbdce342abb5037d32fb06
Author: vernedeng <[email protected]>
AuthorDate: Wed Jul 26 09:38:00 2023 +0800
[INLONG-801][Doc] Add blog for the 1.8.0 release (#814)
Co-authored-by: vernedeng <[email protected]>
---
blog/2023-07-24-release-1.8.0.md | 110 ++++++++++++++++++++
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+---
+title: Release 1.8.0
+author: Verne Deng
+author_url: https://github.com/vernedeng
+author_image_url: https://avatars.githubusercontent.com/u/45282474?v=4
+tags: [Apache InLong, Version]
+---
+
+Apache InLong recently released version 1.8.0, which closed about 190+ issues,
including 6+ major features and 30+ optimizations. The main improvements
include multi-tenant management, support for multiple Apache Flink versions,
data synchronization in Dashboard, data preview support, and optimization of
ultra-long log processing logic. After the release of 1.8.0, Apache InLong has
completed the layout of full-scenario data integration around data access, data
synchronization, and data s [...]
+<!--truncate-->
+
+## About Apache InLong
+As the industry's first one-stop, full-scenario, open-source massive data
integration framework, Apache InLong provides automatic, safe, reliable, and
high-performance data transmission capabilities to facilitate businesses to
build stream-based data analysis, modeling, and applications quickly. At
present, InLong is widely used in various industries such as advertising,
payment, social networking, games, artificial intelligence, etc., serving
thousands of businesses, among which the sca [...]
+
+The core keywords of InLong project positioning are "one-stop" and "massive
data". For "one-stop", we hope to shield technical details, provide complete
data integration and support services, and implement out-of-the-box; With its
advantages, such as multi-cluster management, it can stably support
larger-scale data volumes based on trillions of lines per day.
+
+## Overview of version 1.8.0
+Apache InLong recently released version 1.8.0, which closed about 190+ issues,
including 6+ major features and 30+ optimizations, mainly completing
multi-tenant management, support for multiple Apache Flink versions, data
synchronization in Dashboard, data preview support, and optimization of
ultra-long log processing logic. After the release of 1.8.0, Apache InLong has
completed the layout of full-scenario data integration around data access, data
synchronization, and data subscription, [...]
+
+- Data access: Data access is the process of aggregating data from data
sources to the same storage service for further data querying and analysis;
+- Data synchronization: Data synchronization is the process of establishing
consistency between data sources and target data storage, which can coordinate
data over time;
+- Data subscription: Data subscription provides subscribers with the data they
are authorized to access;
+
+In version 1.8.0 of Apache InLong, many other features have also been
completed, mainly including:
+
+### Agent module
+- Optimized ultra-long log processing logic, improving file collection
efficiency and stability
+- Fixed the issue of thread leakage caused by task termination
+- Adopted flow control to solve the OOM problem caused by file number growth
+
+### DataProxy module
+- Support for Golang SDK
+- Support for configuring black and white lists based on full IP or CIDR
format IP segments
+- Support for configuring the maximum number of write retries
+- Support for sending data to the default Topic when write fails
+- Code refactoring, unified configuration acquisition method
+
+### Sort module
+- Enhanced DDL parsing capability, improving the stability of DDL-aware
scenarios
+- Support for multiple Flink versions
+- Support for Decimal precision recognition in whole-library scenarios
+- Hive supports whole-library migration, with the implementation consistent
with MySQL whole-library migration
+- Iceberg supports automatic column updates and column deletions, greatly
enriching Schema change capabilities
+
+### Manager module
+- Support for Pulsar, TubeMQ data preview
+- Support for dynamic configuration of audit data sources
+- Support for querying audit delay information
+- Support for multi-tenant management
+
+### Dashboard module
+- Support for data flow preview
+- Support for viewing InLongGroup resource details
+- Support for tenant management and tenant switching
+- Support for data synchronization
+
+### Others
+- Remove conflicting Jsqlparser versions
+- Upgrade Spring-Boot-Autoconfigure version to 2.6.15
+- Upgrade the Snappy-Java version to 1.1.10.1
+- Fix syntax errors in Workflow configuration files
+
+## 1.8.0 Feature Introduction
+### Agent optimizes ultra-long log processing logic, improving file collection
efficiency and stability
+In actual use, due to improper use by users or bugs in data production
programs, occasionally, a single data length reaches MB or even GB level. For
Agents deployed in low-profile environments, this type of data greatly affects
the performance of sending. The lower version Agent reads this type of data
directly into memory based on the newline character and then discards it, but
is limited by the hardware configuration of the Agent deployment environment, a
single ultra-long data is extr [...]
+
+
+
+### Agent adopts global flow control, solving the OOM problem caused by the
growth of file numbers
+In previous versions, each file was collected and sent by its thread. Although
we limited the maximum collection buffer of each file, with the growth of user
traffic, the increase in the number of files is inevitable, leading to the
simultaneous collection of too many files, causing OOM exceptions due to memory
overflow. InLong supports the feature of Agent configuring global flow control
in version 1.8.0. With this feature, Agent can effectively avoid frequent OOM
problems caused by the [...]
+
+
+### Support multiple Flink versions
+As community users go deeper into using InLong, the scenarios InLong faces
become more diverse and complex. To support the needs of users in different
Flink environments, InLong has added support for multiple Flink versions in the
current version. Users can choose the Flink version to start in the
plugins/flink-sort-plugin.properties configuration file in InLong-Manager.
+
+When changing the Flink version required to run the Sort component, you also
need to replace the connectors in the InLong-Sort/connector directory with the
corresponding version of the jar package. For details, see the InLong official
website documentation. Thanks to @Emsnap, @GanfengTan, and @haifxu for their
contributions to this capability.
+```
+# inLong-manager/plugins/flink-sort-plugin.properties
+
+# Flink version, support [1.13|1.15]
+flink.version=1.13
+```
+
+### Support multi-tenant management
+To address the requirements for permission and resource isolation in
multi-user scenarios, InLong introduces a multi-tenant architecture in the
current version. The multi-tenant architecture ensures that data and
permissions do not interfere with each other among different users within the
same group of services. Thanks to @vernedeng and @bluewang for their
contributions to this feature, see INLONG-7914 for feature details. The
following is the core process:
+
+
+Tenants are transparent to core logic developers. At the entrance of the
request, tenant authentication is added, and requests without access to the
tenant's permissions are directly rejected; before accessing the Database, the
corresponding tenant filter conditions are added to ensure that the scope of
data query and modification is limited within the tenant.
+
+Users can create tenants and assign tenant roles on the Dashboard.
+
+
+### Support real-time synchronization
+The new version supports real-time data synchronization. The main difference
between real-time synchronization and data access is that it does not require
the support of intermediate MQ storage. The Sort component directly stores the
source data, greatly enriching the user's usage scenarios.
+
+As shown in the figure below, the Tab page adds a "Data Synchronization"
label. After the user configures the basic Group information, they only need to
enter the "Data Source" and "Data Target" information, and after submitting the
task, the data can be synchronized in real-time.
+
+Thanks to @fuwen11, @bluewang, @Emsnap, and @haifxu for their contributions to
this feature.
+
+
+### Support data preview
+For businesses just accessing InLong, data preview can help users quickly
confirm the accuracy of reported data and locate problems. In this version, the
InLong front supports previewing users' real-time reported data. Thanks to
@fuwen11 and @bluewang's contributions, users can choose data preview in the
operation bar under the data stream after successfully creating a data stream
and reporting data.
+
+
+### Support querying transmission delay
+Transmission delay is crucial for some real-time consumption scenarios. In
this version, InLong audit supports frontend viewing of average transmission
delay indicators. Thanks to @fuwen11 and @bluewang's contributions, users can
query link transmission delay after successfully creating a data stream and
reporting data.
+
+
+## Follow-up planning
+In version 1.8.0, the community also restructured the DataProxy code, unified
the configuration pull interface, supported complete IP and CIDR-based IP
segment configuration of black and white list features, and improved module
performance and stability. Sort has improved stability in DDL sensing scenarios
and supports whole library migration of Hive, Iceberg automatic column update,
and column storage features. In subsequent versions, InLong will refactor
DataProxy C++ SDK, enrich Flink [...]
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diff --git
a/i18n/zh-CN/docusaurus-plugin-content-blog/2023-07-24-release-1.8.0.md
b/i18n/zh-CN/docusaurus-plugin-content-blog/2023-07-24-release-1.8.0.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,111 @@
+---
+title: Release 1.8.0
+author: Verne Deng
+author_url: https://github.com/vernedeng
+author_image_url: https://avatars.githubusercontent.com/u/45282474?v=4
+tags: [Apache InLong, Version]
+---
+
+Apache InLong（应龙） 最近发布了 1.8.0 版本，该版本关闭了约 190+ 个issue，包含 6+ 个大特性和 30+
个优化，主要完成了多租户管理、支持 Apache Flink 多版本、Dashboard 增加数据同步、支持数据预览、优化超长日志处理逻辑等。1.8.0
发布后，Apache InLong 围绕数据接入、数据同步和数据订阅的全场景数据集成布局基本完成，配合多租户管理、多集群管理、审批流管理、全链路审计/指标等。
+<!--truncate-->
+
+## 关于 Apache InLong
+作为业界首个一站式、全场景海量数据集成框架，Apache InLong（应龙）
提供了自动、安全、可靠和高性能的数据传输能力，方便业务快速构建基于流式的数据分析、建模和应用。目前 InLong
正广泛应用于广告、支付、社交、游戏、人工智能等各个行业领域，服务上千个业务，其中高性能场景数据规模超百万亿条/天，高可靠场景数据规模超十万亿条/天。
+
+InLong
项目定位的核心关键词是“一站式”、“全场景”和“海量数据”。对于“一站式”，我们希望屏蔽技术细节、提供完整数据集成及配套服务，实现开箱即用；对于“全场景”，我们希望提供全方位的解决方案，覆盖大数据领域常见的数据集成场景；对于“海量数据”，我们希望通过架构上的数据链路分层、全组件可扩展、自带多集群管理等优势，在百万亿条/天的基础上，稳定支持更大规模的数据量。
+
+## 1.8.0 版本总览
+Apache InLong（应龙） 最近发布了 1.8.0 版本，该版本关闭了约 190+ 个issue，包含 6+ 个大特性和 30+
个优化，主要完成了多租户管理、支持 Apache Flink 多版本、Dashboard 增加数据同步、支持数据预览、优化超长日志处理逻辑等。1.8.0
发布后，Apache InLong
围绕数据接入、数据同步和数据订阅的全场景数据集成布局基本完成，配合多租户管理、多集群管理、审批流管理、全链路审计/指标等，Apache InLong
搭建完成全方位的数据集成解决方案，实现开箱机用：
+
+- 数据接入：数据接入是将数据从数据源汇聚到同一个存储服务的过程，可用于进一步数据查询和分析；
+- 数据同步：数据同步是建立数据源和目标数据存储之间一致性的过程，可随着时间持续协调数据；
+- 数据订阅：数据订阅为订阅者提供他们有权访问的数据；
+
+Apache InLong 1.8.0 版本中，还完成了大量其它特性，主要包括：
+
+### Agent 模块
+- 优化超长日志处理逻辑，提升文件采集效率和稳定性
+- 修复因任务停止导致线程泄漏的问题
+- 采用流量控制，解决文件数增长导致的 OOM 问题
+
+### DataProxy 模块
+- 支持 Golang SDK
+- 支持基于完整 IP 或 CIDR 格式的 IP 段配置黑白名单
+- 支持配置写入最大重试次数
+- 支持配置写入失败时将数据发送到缺省 Topic
+- 代码重构，统一配置获取方式
+
+### Sort 模块
+- 增强了 DDL 的解析能力, 提升 DDL 感知场景的稳定性
+- 支持 Flink 多版本
+- 整库场景下支持 Decimal 的精度识别
+- Hive 支持整库迁移，实现方式与 mysql 整库迁移保持一致
+- Iceberg 支持自动列更新和列删除，极大丰富了 Schema 变更能力
+
+### Manager 模块
+- 支持 Pulsar、TubeMQ 数据预览
+- 支持动态配置审计数据源
+- 支持查询审计延迟信息
+- 支持多租户管理
+
+### Dashboard 模块
+- 支持流向数据预览
+- 支持 InLongGroup 查看资源详情
+- 支持租户管理和租户切换
+- 支持数据同步
+
+### 其它
+- 移除 Jsqlparser 冲突版本
+- 升级 Spring-Boot-Autoconfigure 版本到 2.6.15
+- 升级 Snappy-Java 版本到 1.1.10.1
+- 修复 Workflow 配置文件语法错误
+
+## 1.8.0 版本特性介绍
+### Agent 优化超长日志处理逻辑，提升文件采集效率和稳定性
+在实际使用中，由于用户使用不当或数据生产程序 bug 等问题，偶发出现单条数据长度达到 MB 甚至 GB 级别。 对于部署在低配环境的 Agent
而言，这类数据极大影响了发送的性能。 低版本 Agent 根据换行符将这类数据直接读到内存中再丢弃，但受限于 Agent 部署环境硬件配置，
单条超长数据极易导致 OOM 异常。 在 1.8.0 版本中， Agent 优化了超长日志的处理逻辑，
通过分段采集、分段丢弃的方式保证数据加载不会超过内存限制。 感谢 @justinhuang 的贡献，详情可见 INLONG-8180。
+
+
+
+### Agent 采用全局流控，解决文件数增长导致的 OOM 问题
+在之前版本中，每个文件分别由各自的线程负责采集和发送。虽然我们限制了每个文件的最大采集
buffer，但是随着用户流量的增长，文件数的增加难以避免，进而导致同时采集文件数过多，打爆内存引发 OOM 异常。InLong 在 1.8.0 版本中支持
Agent 配置全局流量控制的特性，利用该特性，Agent 可以有效避免因为文件数增长或者采用小配额服务器导致的频繁 OOM 的问题，感谢
@justinhuang 的贡献，详情可见 INLONG-8251。如果需要使用该特性，可以在 agent.properties 中增加相应配置。
+
+
+### 支持 Flink 多版本
+随着社区用户的深入使用，InLong 面对的场景也更加多样化和复杂化。为了支持不同 Flink 环境的用户需求，InLong 在当前版本增加了支持
Flink 多版本的特性，用户可以在 InLong-Manager 的 plugins/flink-sort-plugin.properties
配置文件中选择启动的flink 版本。
+
+更换运行 Sort 组件所需要的 Flink 版本时，也需要更换 InLong-Sort/connector 目录中的 connectors 为对应版本的
jar 包，详情可以查看 InLong 官网文档。感谢 @Emsnap，@GanfengTan 和 @haifxu 对该能力的贡献。
+```
+# inLong-manager/plugins/flink-sort-plugin.properties
+
+# Flink version, support [1.13|1.15]
+flink.version=1.13
+```
+
+### 支持多租户管理
+为了解决多用户场景下对于权限和资源隔离性的要求，InLong
在当前版本引入了多租户架构。多租户架构能够在同一组服务下，确保不同用户间数据和权限互不干扰。感谢 @vernedeng 和 @bluewang
对该功能的贡献，特性详情可见 INLONG-7914。下图为核心流程：
+
+
+租户对于核心逻辑开发者而言是透明的。在请求的入口处，增加了租户鉴权，对于没有访问该租户权限的请求直接驳回；在访问 Database
前，增加对应的租户过滤条件，确保数据的查询和修改范围被限制在该租户内。
+
+用户可以在 Dashboard 上完成租户的创建，租户角色分配等操作。
+
+
+### 支持实时同步
+新版本中支持了数据的实时同步，实时同步与数据接入的主要区别是不需要中间 MQ 存储的支持，由 Sort 组件直接将源端数据入库，极大丰富了用户的使用场景。
+
+如下图所示，Tab 页新增 “数据同步” 标签，用户配置完基本 Group 信息后只需要输入 “数据来源” 以及 “数据目标”
信息即可，提交任务后便可实现数据的实时同步。
+
+感谢 @fuwen11 、@bluewang 、@Emsnap 、@haifxu 对此功能的贡献。
+
+
+### 支持数据预览
+对于刚接入 InLong 的业务而言，数据预览能够帮助用户快速确认上报数据的准确性以及定位问题。在该版本中，InLong
前端支持预览用户实时上报的数据。感谢 @fuwen11 和 @bluewang 的贡献，用户在成功创建数据流并上报数据后，可以在数据流下的操作栏选择数据预览。
+
+
+### 支持查询链路传输时延
+传输时延对于某些实时消费场景至关重要。在该版本中，InLong 审计支持前端查看平均传输时延指标。感谢 @fuwen11 和 @bluewang
的贡献，用户在成功创建数据流并上报数据后， 可以查询链路传输时延。
+
+
+## 后续规划
+在 1.8.0 版本中，社区还重构了 DataProxy 代码，统一了配置拉取接口，支持完整 IP 和基于 CIDR 的 IP
段配置黑白名单的特性，提升了模块性能和稳定性。 Sort 在 DDL 感知场景的稳定性有所提升， 同时支持 Hive 整库迁移， Iceberg
自动列更新和列存储等特性。 在后续的版本中，InLong 将重构 DataProxy C++ SDK、丰富 Flink 1.15
Connector、完善数据同步功能等，期待更多开发者参与贡献。
+
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