May 2025
Intermediate to advanced
452 pages
6h 3m
Japanese
Content preview from Apache Spark によるストリーム処理
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第V部 Apache Sparkを超えて
このパートでは、Apache Sparkのストリーミング・エンジンをより広い範囲から見ていきたい。 まず、分散ストリーム処理業界の他の関連プロジェクトとの詳細な比較から始め、Sparkがどこから来たのか、そしてSparkのような代替手段がないことを説明する。
我々は、以下のような他の分散処理エンジンについて簡単に説明し、重点的に比較する：
- アパッチ・ストーム
-
分散処理の歴史的なランドマークであり、今日でもその足跡を残しているシステムである。
- Apache Flink
-
Sparkの最も活発な競合である分散ストリーム処理エンジンである。
- Apache Kafkaストリーム
-
信頼性の高い分散ログおよびストリーム・コネクタで、分析能力の開発が速い。
また、主要プレーヤー（AmazonとMicrosoft）が提供するクラウドや、Google Cloud Dataflowの一元化エンジンについても触れる。
Apache Sparkのストリーミングの可能性と課題について詳しく学んだ後、Apache Sparkによるストリーム処理の実践コミュニティとエコシステムにどのように参加できるかについて触れ、ストリーミング分析の実践において貢献し、議論し、成長するためのリファレンスを提供する。
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.