- Oct 2024
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www.youtube.com www.youtube.com
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1:23:30 How can a neighbourhood become a local food PRODUCER evolving into a PROSUMER
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- May 2024
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cfe.tiff.net cfe.tiff.net
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Producer: Stephen Hegyes, Rose Waddell
Producer
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- Apr 2024
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for - podcast channel, youtube channel - Andrew Huberman - neuroscience - theme - science-based tools for everyday life - interview with - music producer Rick Ruben - podcast title - How to access your creativity
summary - Although Rick Ruben's field is music production, he shares his perspective on creativity
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- Nov 2023
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Economies that are heavily reliant on oil and gas revenues face some stark choices and pressures in energy transitions.
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for: stats - oil and gas - steep drop in revenues of fossil fuel producer economies
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stats: oil and gas - steep drop in revenues of fossil fuel reliant economies
- per capita net income from oil and natural gas among producer economies will be 60% lower in 2030 in a 1.5 °C scenario.relative to revenues between 2010 and 2022.
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question
- many producer economies are not diversifying into clean energy fast enough to compensate for these steep revenue drops
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- Oct 2023
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www.linkedin.com www.linkedin.com
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“It’s the consumer who contributes to increasing CO2 emissions, not the producer.”
- for: climate change - individual change, producer-consumer entanglement, big oil, COP28
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- Aug 2023
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developer.confluent.io developer.confluent.io
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Kafka Broker
producer key properties => linger time -> linger.ms batch size -> batch.size
these determine the throughput and latency of kafkaproducers
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- Oct 2021
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lt.wikipedia.org lt.wikipedia.org
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Jurgis Pranas Didžiulis Valencia (born 5 November 1979 in Bogotá , Colombia ) is a performer, song and music author, producer, public figure and activist.
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- Aug 2021
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psyarxiv.com psyarxiv.com
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Chen, Cathy Xi, Gordon Pennycook, and David Rand. ‘What Makes News Sharable on Social Media?’ PsyArXiv, 9 July 2021. https://doi.org/10.31234/osf.io/gzqcd.
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- Apr 2021
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www.politico.eu www.politico.eu
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Deutsch, J., & Barigazzi, J. (2021, April 21). EU preparing legal case against AstraZeneca over vaccine shortfalls. POLITICO. https://www.politico.eu/article/eu-preparing-legal-case-against-astrazeneca-over-vaccine-shortfalls/
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- Mar 2021
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covid-19.iza.org covid-19.iza.org
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Balleer, A., Link, S., Menkhoff, M., & Zorn, P. (2020). Demand or Supply? Price Adjustment during the COVID-19 Pandemic. IZA Discussion Paper, 13568.
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- Oct 2020
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studybreaks.com studybreaks.com
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Richard Curtis
Richard Curtis is a screenwriter, producer and film director. He produced Love Actually, Bridget Jone's Diary, Notting Hill and many more rom-coms
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- May 2020
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www.bps.org.uk www.bps.org.uk
- Jun 2017
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www.confluent.io www.confluent.io
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You measure the throughout that you can achieve on a single partition for production (call it p) and consumption (call it c). Let’s say your target throughput is t.
t = throughput (QPS) p = single partition for production c = consumption
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sookocheff.com sookocheff.com
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By electing a new leader as soon as possible messages may be dropped but we will minimized downtime as any new machine can be leader.
two scenarios to get the leader back: 1.) Wait to bring the master back online. 2.) Or elect the first node that comes back up. But in this scenario if that replica partition was a bit behind the master then the time from when this replica went down to when the master went down. All that data is Lost.
SO there is a trade off between availability and consistency. (Durability)
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keep in mind that these guarantees hold as long as you are producing to one partition and consuming from one partition.
This is very important a 1-to-1 mapping between writer and reader with partition. If you have more producers per partition or more consumers per partition your consistency is going to go haywire
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www.confluent.io www.confluent.io
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The high watermark is the offset of the last message that was successfully copied to all of the log’s replicas.
High Watermark: messages copied over to log replicas
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github.com github.com
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incidents are an unavoidable reality of working with distributed systems, no matter how reliable. A prompt alerting solution should be an integral part of the design,
see how it can hook into the current logging mechanism
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- May 2017
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medium.com medium.com
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More events may arrive late for various reasons, we need to handle late-arrived events consistently.
May not be needed for our use case.
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www.quora.com www.quora.com
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With Flume & FlumeNG, and a File channel, if you loose a broker node you will lose access to those events until you recover that disk.
In flume you loose events if the disk is down. This is very bad for our usecase.
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kafka.apache.org kafka.apache.org
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The Kafka cluster retains all published records—whether or not they have been consumed—using a configurable retention period. For example, if the retention policy is set to two days, then for the two days after a record is published, it is available for consumption, after which it will be discarded to free up space. Kafka's performance is effectively constant with respect to data size so storing data for a long time is not a problem.
irrespective of the fact that the consumer has consumed the message that message is kept in kafka for the entire retention policy duration.
You can have two or more consumer groups: 1 -> real time 2 -> back up consumer group
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Kafka for Stream Processing
Could be something we can consider for directing data from a raw log to a tenant based topic.
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replication factor N, we will tolerate up to N-1 server failures without losing any records
Replication Factor means number of nodes/brokers which could go down before we start losing data.
So if you have a replication factor of 6 for a 11 node cluster, then you will be fault tolerant till 5 nodes go down. After that point you are going to loose data for a particular partition.
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Messages sent by a producer to a particular topic partition will be appended in the order they are sent. That is, if a record M1 is sent by the same producer as a record M2, and M1 is sent first, then M1 will have a lower offset than M2 and appear earlier in the log.
ordering is guaranteed.
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sookocheff.com sookocheff.com
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The offset the ordering of messages as an immutable sequence. Kafka maintains this message ordering for you.
Kafka maintains the ordering for you...
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kafka.apache.org kafka.apache.org
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The producer is responsible for choosing which record to assign to which partition within the topic.
Producer can publish to a specific topics
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individual partition must fit on the servers that host it
Each Partition is bounded by the server that hosts that partition.
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the only metadata retained on a per-consumer basis is the offset or position of that consumer in the log. This offset is controlled by the consumer: normally a consumer will advance its offset linearly as it reads records, but, in fact, since the position is controlled by the consumer it can consume records in any order it likes.
partition offset maintained by kafka. Offset number is maintained so that if the consumer goes down nothing breaks.
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