Tag archive

#stream-processing

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4 articles

Windowing in Stream Processing: Tumbling, Sliding, and Session Windows

Windowing in Stream Processing: Timing is Everything In stream processing (Kafka Streams, Flink, Spark Streaming), you rarely want to aggregate data from the beginning of time. Instead, you want to perform calculations o…

Apr 20, 20262 min read

Deep Dive

#stream-processing#kafka-streams#flink

System DesignAdvanced

System Design: Designing a Real-Time Analytics Dashboard

System Design: Designing a Real-Time Analytics Dashboard Real-time analytics dashboards (used for tracking game players, ad clicks, or server metrics) require capturing and visualizing massive data streams. The challenge…

Apr 20, 20262 min read

Deep Dive

#system-design#analytics#real-time

System DesignAdvanced

System Design: Solving the Top K Problem (Heavy Hitters)

System Design: Solving the Top K Problem The "Top K" problem (or Heavy Hitters) is about finding the $ most frequent items in a massive stream of data. For example: - YouTube: The top 10 trending videos in the last hour.…

Apr 20, 20263 min read

Deep Dive

#system-design#top-k#heavy-hitters

Data EngineeringAdvanced

Kafka Streams: Real-Time Stream Processing Without a Separate Cluster

Kafka Streams is a Java library for building real-time stream processing applications. Unlike Flink or Spark Streaming, it has no separate cluster — it runs as a library inside your Java application. Each instance of you…

Apr 24, 20256 min read

Deep Dive

#kafka#kafka streams#stream processing