Skip to main content

Flume 1.2.0 released

By Anonymous
Listen:

The Apache Flume Team released yesterday the next large release with number 1.2.0. Here a overview about the fixes and additions (thanks Mike, I copy your overview):

Apache Flume 1.2.0 is the third release under the auspices of Apache of the so-called "NG" codeline, and our first release as a top-level Apache project! Flume 1.2.0 has been put through many stress and regression tests, is stable, production-ready software, and is backwards-compatible with Flume 1.1.0. Four months of very active development went into this release: a whopping 192 patches were committed since 1.1.0, representing many features, enhancements, and bug fixes. While the full change log can be found in the link below, here are a few new feature highlights:

* New durable file channel 
* New client API 
* New HBase sinks (two different implementations) 
* New Interceptor interface (a plugin processing API) 
* New JMX-based monitoring support

With this release - the first after evolving into a tier 1 Apache project - we've updated the website and firstly have a well written UserGuide (again thanks to Mike and Ralph for their great effort).

User-Guide: http://flume.apache.org/FlumeUserGuide.html
Api-Documention:  http://flume.apache.org/releases/content/1.2.0/apidocs/

What's the next?
Now, we got a increasing interest into a Windows version. I don't know why, but that's happen. I try to port some of the sinks into a Windows Platform - if you're a Windows Developer and you've time to spent into the project, all hands are welcome.
















Labels:






























Comments











Post a Comment



















Popular posts from this blog



















Deal with corrupted messages in Apache Kafka












By
























Under some strange circumstances it can happen that a message in a Kafka topic is corrupted. This happens often by using 3rd party frameworks together with Kafka. Additionally, Kafka < 0.9 has no lock at Log.read() at the consumer read level, but has a lock on Log.write(). This can cause a rare race condition, as described in KAKFA-2477 [1]. Probably a log entry looks like:   ERROR Error processing message, stopping consumer:  (kafka.tools.ConsoleConsumer$) kafka.message.InvalidMessageException: Message is corrupt (stored crc = xxxxxxxxxx, computed crc = yyyyyyyyyy    Kafka-Tools  Kafka stores the offset of every consumer in Zookeeper. To read out the offsets, Kafka provides handy tools [2]. But also zkCli.sh can be used, at least to display the consumer and the stored offsets. First we need to find the consumer for a topic (> Kafka 0.9):  bin/kafka-consumer-groups.sh --zookeeper management01:2181 --describe --group test  Prior to Kafka 0.9 the only possibility to get this inform




















Post a Comment









Read more




























Hive query shows ERROR "too many counters"












By


Anonymous




















A hive job face the odd " Too many counters:"  like   Ended Job = job_xxxxxx with exception 'org.apache.hadoop.mapreduce.counters.LimitExceededException(Too many counters: 201 max=200)' FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.MapRedTask Intercepting System.exit(1)     These happens when operators are used in queries ( Hive Operators ). Hive creates 4 counters per operator, max upto 1000, plus a few additional counters like file read/write, partitions and tables. Hence the number of counter required is going to be dependent upon the query.     To avoid such exception, configure " mapreduce.job.counters.max " in mapreduce-site.xml  to a value above 1000. Hive will fail when he is hitting the 1k counts, but other MR jobs not. A number around 1120 should be a good choice.    Using " EXPLAIN EXTENDED " and " grep -ri operators | wc -l " print out the used numbers of operators. Use this value to tweak the MR s




















2 comments









Read more




























Life hacks for your startup with OpenAI and Bard prompts












By
























OpenAI  and Bard   are the most used GenAI tools today; the first one has a massive Microsoft investment, and the other one is an experiment from Google. But did you know that you can also use them to optimize and hack your startup?  For startups, reating pitch scripts, sales emails, and elevator pitches with one (or both) of them helps you not only save time but also validate your marketing and wording. Curios? Here a few prompt hacks for startups to create / improve / validate buyer personas, your startups mission / vision statements, and USP definitions. First Step: Introduce yourself and your startup Introduce yourself, your startup, your website, your idea, your position, and in a few words what you are doing to the chatbot: Prompt : I'm NAME and our startup NAME, with website URL, is doing WHATEVER. With PRODUCT NAME, we aim to change or disrupt INDUSTRY. Bard is able to pull information from your website. I'm not sure if ChatGPT can do that, though. But nevertheless, now




















Post a Comment









Read more