mesos-chronos | 易学教程

Mesos task - Failed to accept socket: future discarded

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问题 I am just trying to upgrade mesos version to 1.3.1 from 1.0.3. Chronos scheduler is able to schedule the JOB thru mesos. The job runs fine and able to see mesos stdout logs. But, still seeing the following in mesos stderr logs. The docker jobs runs fine, but still the status is showing as failed with the below logs. I0905 22:05:00.824811 456 exec.cpp:162] Version: 1.3.1 I0905 22:05:00.829165 459 exec.cpp:237] Executor registered on agent c63c93dc-3d9f-4322-9f82-0553fd1324fe-S0 E0905 22:05:11

Isn't chronos a centralized scheduler?

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问题 Why chronos is called as distributed and fault-tolerant scheduler? As per my understanding there is only one scheduler instance running that manages job schedules. As per Chronos doc, internally, the Chronos scheduler main loop is quite simple. The pattern is as follows: Chronos reads all job state from the state store (ZooKeeper) Jobs are registered within the scheduler and loaded into the job graph for tracking dependencies. Jobs are separated into a list of those which should be run at the

Scheduling spark jobs on a timely basis

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问题 Which is the recommended tool for scheduling Spark Jobs on a daily/weekly basis. 1) Oozie 2) Luigi 3) Azkaban 4) Chronos 5) Airflow Thanks in advance. 回答1: Updating my previous answer from here: Suggestion for scheduling tool(s) for building hadoop based data pipelines Airflow: Try this first. Decent UI, Python-ish job definition, semi-accessible for non-programmers, dependency declaration syntax is weird. Airflow has built in support for the fact that jobs scheduled jobs often need to be

Scheduling spark jobs on a timely basis

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Which is the recommended tool for scheduling Spark Jobs on a daily/weekly basis. 1) Oozie 2) Luigi 3) Azkaban 4) Chronos 5) Airflow Thanks in advance. Joe Harris Updating my previous answer from here: Suggestion for scheduling tool(s) for building hadoop based data pipelines Airflow: Try this first. Decent UI, Python-ish job definition, semi-accessible for non-programmers, dependency declaration syntax is weird. Airflow has built in support for the fact that jobs scheduled jobs often need to be rerun and/or backfilled. Make sure you build your pipelines to support this. Azkaban: Nice UI,

Apache Chronos Architecture Explaination

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问题 I was trying to see what makes Chronos better than Crons? I am not able to understand its job scheduling and executing architecture completely. Specifically, these are the questions around chronos architecture that are not clear to me. In one of the Chronos documentation I read that since crons has SPoF, crons are bad and cronos is better. How chronos avoids SPoF? Where are job schedules saved in Chronos? Does it maintain some sort of DB for that? How scheduled jobs are triggered, who sends

Apache Chronos Architecture Explaination

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I was trying to see what makes Chronos better than Crons? I am not able to understand its job scheduling and executing architecture completely. Specifically, these are the questions around chronos architecture that are not clear to me. In one of the Chronos documentation I read that since crons has SPoF, crons are bad and cronos is better. How chronos avoids SPoF? Where are job schedules saved in Chronos? Does it maintain some sort of DB for that? How scheduled jobs are triggered, who sends an event to Chronos to trigger the job? Are dependent jobs triggered by chronos, if yes how chronos even