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@ Apache Kafka A Streaming Data Platform
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@ @gamussa @confluentinc Solutions Architect Developer Advocate @gamussa in internetz Hey you, yes, you, go follow me in twitter © Who am I?
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@ @gamussa @confluentinc A company is build on DATA FLOWS but All we have is DATA STORES
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc Streaming Platform 1. Pub/Sub 2. Store 3. Process
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@ @gamussa @confluentinc Streaming Platform 1. Pub/Sub 2. Store 3. Process
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@ @gamussa @confluentinc Core abstraction DB - table Hadoop - file Messaging -?
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@ @gamussa @confluentinc LOGS
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@ @gamussa @confluentinc Producing to Kafka Time
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@ @gamussa @confluentinc Producing to Kafka Time C C C
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@ @gamussa @confluentinc Producing to Kafka - With Key Time A B C D hash(key) % numPartitions = N
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@ @gamussa @confluentinc Producing to Kafka - No Key Time Messages will be produced in a round robin fashion
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@ @gamussa @confluentinc Consuming From Kafka - Single Consumer C
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@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers C C C1 C C C2
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@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers C C C C
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@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers 0 1 2 3
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@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers 0 1 2 3
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@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers 0, 3 1 2 3
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@ @gamussa @confluentinc Producers Consumers
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc Kafka Connect does hard work so you don’t 1. Scale out
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc Streaming Platform 1. Pub/Sub 2. Store 3. Process
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@ @gamussa @confluentinc Why Store?
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@ @gamussa @confluentinc Scalability of a filesystem Throughput 100s mb/s TBs per server Commodity Hardware O(1) writes
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@ @gamussa @confluentinc Guarantees of a database Persistence Strict ordering
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@ @gamussa @confluentinc Replication Fault Tolerance Partitioning Scale Distributed by Design
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc Partition Leadership and Replication Broker 1 Topic1 partition1 Broker 2 Broker 3 Broker 4 Topic1 partition1 Topic1 partition1 Leader Follower Topic1 partition2 Topic1 partition2 Topic1 partition2 Topic1 partition3 Topic1 partition4 Topic1 partition3 Topic1 partition3 Topic1 partition4 Topic1 partition4
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@ @gamussa @confluentinc Partition Leadership and Replication - node failure Broker 1 Topic1 partition1 Broker 2 Broker 3 Broker 4 Topic1 partition1 Topic1 partition1 Leader Follower Topic1 partition2 Topic1 partition2 Topic1 partition2 Topic1 partition3 Topic1 partition4 Topic1 partition3 Topic1 partition3 Topic1 partition4 Topic1 partition4
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@ @gamussa @confluentinc Streaming Platform 1. Pub/Sub 2. Store 3. Process
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@ @gamussa @confluentinc What is Stream Processing? A machine for combining streams of events
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc https://www.confluent.io/download/
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@ @gamussa @confluentinc We are hiring! https://www.confluent.io/careers/
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@ @gamussa @confluentinc One more thing…
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc
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@ @gamussa @confluentinc A Major New Paradigm
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@ @gamussa @confluentinc Thanks! questions? @gamussa viktor@confluent.io We are hiring! https://www.confluent.io/careers/