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61 строка
3.5 KiB
Plaintext
61 строка
3.5 KiB
Plaintext
2022
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https://habr.com/ru/company/yandex_praktikum/blog/700608/
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IFMO - Suhovitskiy - Software Projecting 18 - Messaging - RabbitMQ, Kafka of 1:34:57
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https://www.youtube.com/watch?v=NyAr11UYKRY
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Suhovitskiy - Messaging Architecture, Kafka and Rabbit 56:00 of 2:27:27
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https://www.youtube.com/watch?v=jgpZBpDMaxQ
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YandexPracticum - Suhovitskiy - Message Brokers Fight ru of 1:57:06
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https://www.youtube.com/watch?v=ZPDn7tdP6Rk
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! 14:50 Nastya Boshnyakovich, Rabbit
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! AMQP, exchange, routing, queues (!!! they push messages to consumers)
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! right projecting pattern is then queues are created by consumer itself
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! Fanout Exch (without routing, -> to all queues)
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! Direct Exch (routing by key)
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! Topic Exch (routing by key with regexp)
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! Headers Exch
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! combining distinct types of exchanges
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! Queue settings (durable - save on disk, exclusive - only one subscriber,
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! autodelete - delete self when all subscribers unsubscribe)
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! +: easy to develop and administer, tune routing in the process,
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! -: high-load problems, horizontal scalability difficulties, either speed or agility-of-routing
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! we can use Rabbit if it is important to
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! - the fact of obtaining message itself
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! - order of messages
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! 23:00 - Dima Shelamov, Kafka
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! till 2018 Rabbit was popular
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! after 2020
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! Data is stored as partitions at disk, working with them by "commit log"
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! Partitions are grouped by sense into topics (close analog to rabbit queues)
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! this allows us to store distinct partitions at distinct servers
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! this allows us to "shard" topic
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! ! Any single partition can be read by only one consumer (maximum)
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! ! data is always aligned inside partition (from left to right as a natural order of the queue)
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! ! subscribers can read partitions with distinct speed
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! Data is persistent, configurable clean-up politics
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! Subscribers do pull messages
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! Messages are stored in partitions for a limited period of time
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! - either till certan configured time threshold
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! - or till partition will grow for a certain amount of disk space
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! - persistence allow us to re-read them, read by chunks
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! We use pull in Kafka (vs Push in Rabbit by single-one msg)
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! Publisher decides to which partition of topic he puts message
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! ! Again: consumer can read only from one partition
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! -> very important Kafka rule: number of partition should be equal
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! to the number of parallel (concurrent) consumers or replics
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! Kafka is a simple thing: it just stores messages and takes them back
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! +: speed and scalability, message replay/re-read, possibility to read messages by batches
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! ... transactionality is added by kafka streams ...
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! -: broken messages processing (no DLQ), Need to account for the last readen message id in partition for each reader
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! Each partition can be replicated multi-times (with the help of keeper)
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! Keeper is reponsible for unique topics naming in cluster, keeps consensus, ...
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! !!! Not nodes, but partitions are master/slave
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! 48:00 Alexander Peredery - Amazon SQS/SNS (simple notif-n service like fanout -> passes further)
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! thematical literature review at the end
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https://habr.com/ru/company/southbridge/blog/666326/
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2021
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TechPrimers - RabbitMQ vs Kafka | Trade-off's to choose one over other of 14:31
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https://www.youtube.com/watch?v=GMmRtSFQ5Z0
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2020
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DataOps Poland #15 Apache Kafka and RabbitMQ from a use-case perspective of 54:48
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https://www.youtube.com/watch?v=dNEnfQIXk7s
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