Enlace del recurso

Tabla de Contenidos: “…KAFKA NO ESTÁ EN UNA DE LAS DOS ORILLAS, (...) -- 2.1 ¿ESTÉTICA ESTALINISTA EN BRECHT? …”

Materias: “…Kafka, Franz, 1883-1924…”

Materias: “…Kafka, Franz, 1883-1924…”

Materias: “…Kafka, Franz, 1883-1924 Entrevistas…”

Materias: “…Kafka, Franz, 1883-1924 Entrevistas…”

Materias: “…Kafka, Franz, 1883-1924…”

Materias: “…Kafka, Franz, 1883-1924 Intervius…”

“…Learn in detail about Apache Kafka platform, which is used by giants such as Netflix and LinkedIn. …”

“…In this video course, host Gwen Shapira from Cloudera shows developers and administrators how to integrate Kafka into a data processing pipeline. You’ll start with Kafka basics, walk through code examples of Kafka producers and consumers, and then learn how to integrate Kafka with Hadoop. …”

Tabla de Contenidos: “…Part 1. Getting started with Kafka streams. Welcome to Kafka streams -- Kafka quickly -- Part 2. …”

Materias: “…Apache Kafka (computer program)…”

Tabla de Contenidos: “…Intro -- Table of Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Chapter 1: Storage Usage in Kafka: Challenges, Strategies, and Best Practices -- How Kafka Runs Out of Disk Space -- A Retention Policy Can Cause Data Loss -- Configuring a Retention Policy for Kafka Topics -- Managing Consumer Lag and Preventing Data Loss -- Handling Bursty Data Influx from Producers -- Balancing Consumer Throttling and Avoiding Unintended Lag -- Understanding Daily Traffic Variations and Their Impact on Data Retention -- Ensuring Batch Duration Compliance with Topic Retention to Avoid Data Loss -- Adding Storage to Kafka Clusters -- When the Cluster Is On-Prem -- Scaling Up -- Scaling Out -- When the Cluster Is in the Cloud -- EBS Disks -- NVME Disks (Ephemeral Disks) -- Strategies and Considerations for Extended Retention in Kafka Clusters -- Calculating Storage Capacity Based on Time-Based Retention -- Retention Monitoring -- Data Skew in Partitions -- Message Rate Into Topic -- Don't Write to the / Mount Point -- Summary -- Chapter 2: Strategies for Aggregation, Data Cardinality, and Batching -- Balancing Message Distribution and Aggregation for Optimal Kafka Performance -- Tuning Parameters to Increase Throughput and Reduce Latency -- Optimizing Producer and Broker Performance: The Impact of Tuning linger.ms and batch.size in Kafka -- Understanding Compression Rate -- The Effect of Data Cardinality on Producers, Consumers, and Brokers -- Defining Data Cardinality -- Effects of High Data Cardinality -- Reducing Cardinality Level and Distribution -- Duplicating Data to Reduce Latency -- Summary -- Chapter 3: Understanding and Addressing Partition Skew in Kafka -- Skew of Partition Leaders vs. …”

Materias: “…Apache Kafka (Electronic resource)…”