国投证券数据开发岗
社招全职信息技术类地点：深圳状态：招聘♡ 收藏
工作描述
任职要求 1、本科及以上学历，计算机、通信、数学等相关专业优先； 2、熟悉 Hadoop、Spark、Flink、Kafka、Starrocks 等大数据平台组件及 MPP 数据库，熟练掌握 Java、Python、SQL 等开发语言； 3、掌握数仓建模理论及落地应用，具备离线或实时数仓建设经验； 4、熟悉常用数据统计、挖掘算法，具备一定的数据分析与建模能力； 5、理解数据驱动…
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包括英文材料
学历+
Hadoop+
https://www.runoob.com/w3cnote/hadoop-tutorial.html
Hadoop 为庞大的计算机集群提供可靠的、可伸缩的应用层计算和存储支持，它允许使用简单的编程模型跨计算机群集分布式处理大型数据集，并且支持在单台计算机到几千台计算机之间进行扩展。
[英文] Hadoop Tutorial
https://www.tutorialspoint.com/hadoop/index.htm
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models.
Spark+
[英文] Learning Spark Book
https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf
This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.
Flink+
https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/learn-flink/overview/
This training presents an introduction to Apache Flink that includes just enough to get you started writing scalable streaming ETL, analytics, and event-driven applications, while leaving out a lot of (ultimately important) details.
https://www.youtube.com/watch?v=WajYe9iA2Uk&list=PLa7VYi0yPIH2GTo3vRtX8w9tgNTTyYSux
Today’s businesses are increasingly software-defined, and their business processes are being automated. Whether it’s orders and shipments, or downloads and clicks, business events can always be streamed. Flink can be used to manipulate, process, and react to these streaming events as they occur.
Kafka+
https://developer.confluent.io/what-is-apache-kafka/
https://www.youtube.com/watch?v=CU44hKLMg7k
https://www.youtube.com/watch?v=j4bqyAMMb7o&list=PLa7VYi0yPIH0KbnJQcMv5N9iW8HkZHztH
In this Apache Kafka fundamentals course, we introduce you to the basic Apache Kafka elements and APIs, as well as the broader Kafka ecosystem.
StarRocks+
https://docs.starrocks.io/docs/quick_start/
These Quick Start guides will help you get going with a small StarRocks environment.
https://itnext.io/introduction-to-starrocks-a-new-modern-analytical-database-1db2177d26e1
Recently, I had the opportunity to explore StarRocks which is the new kid in the block when talking about massive scale databases which are able to handle petabytes of data.
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