Skip to main content

Syncing hdfs-clusters

By Anonymous
Listen:

Mostly it is a good idea to test new code on a reference cluster with a nearly live dataset. To sync files from a cluster to another use the hadoop builtin tool distcp [1]. With a small script I "rebase" a development cluster with logfiles we collected over the past day.

COPYDATE=`date -d '-1 Day' +"%Y-%m-%d"`
DELDATE=`date -d '-3 Day' +"%Y-%m-%d"`
SNAMENODE=namenode1
TNAMENODE=namenode2
PATH="/user/flume/logs"
LOG="/var/log/jobs/sync.log"


#logging
exec >> $LOG 2>&1


echo -e "\n ------- sync $COPYDATE ------- \n"
/usr/bin/hadoop distcp -i -m 100 hdfs://$SNAMENODE:9000/$PATH/$COPYDATE hdfs://$TNAMENODE:9000/$PATH/$COPYDATE/
sleep 60
echo -e "\n ------- delete $DELDATE ------- \n"
/usr/bin/hadoop dfs -rmr /$PATH/$DELDATE
/usr/bin/hadoop dfs -rmr /$PATH/_distcp_logs*
sleep 60
/usr/bin/hadoop dfs -chmod -R 777 /$PATH/

The script copy logfiles from the past day and the given path to the target's hdfs and delete the datasets if they older than 3 days. I didn't want the logs in that directory (and I didn't need them), so I delete them too. We didn't have the user flume in our development cluster, so I set permissions to 777 for the whole directory.
To debug a failure the script writes all output into the given logfile. If you want to rotate the file add a logrote-definition into /etc/logrotate.d/. To decrease the load and network impact at our live cluster I use only 100 maps. The script runs every day via cron 02:00 pm and took for 1TB around 1 hour. Here a ganglia chart for a 300 GB sync.



[1] http://hadoop.apache.org/common/docs/current/distcp.html

Technocrati Claim: PYBPPWZ4RFST
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 often happens when using 3rd party frameworks with Kafka. In addition, Kafka < 0.9 does not have a lock on Log.read() at the consumer read level, but does have a lock on Log.write(). This can lead to a rare race condition as described in KAKFA-2477 [1]. A likely log entry looks like this: 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 each consumer in Zookeeper. To read the offsets, Kafka provides handy tools [2]. But you can also use zkCli.sh, 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 way to get this in...
Post a Comment
Read more

Beyond Ctrl+F - Use LLM's For PDF Analysis

By
PDFs are everywhere, seemingly indestructible, and present in our daily lives at all thinkable and unthinkable positions. We've all got mountains of them, and even companies shouting about "digital transformation" haven't managed to escape their clutches. Now, I'm a product guy, not a document management guru. But I started thinking: if PDFs are omnipresent in our existence, why not throw some cutting-edge AI at the problem? Maybe Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) could be the answer. Don't get me wrong, PDF search indexes like Solr exist, but they're basically glorified Ctrl+F. They point you to the right file, but don't actually help you understand what's in it. And sure, Microsoft Fabric's got some fancy PDF Q&A stuff, but it's a complex beast with a hefty price tag. That's why I decided to experiment with LLMs and RAG. My idea? An intelligent knowledge base built on top of our existing P...
Post a Comment
Read more

Run Llama3 (or any LLM / SLM) on Your MacBook in 2024

By
I'm gonna be real with you: the Cloud and SaaS / PaaS is great... until it isn't. When you're elbow-deep in doing something with the likes of ChatGPT or Gemini or whatever, the last thing you need is your AI assistant starts choking (It seems that upper network connection was reset) because 5G or the local WiFi crapped out or some server halfway across the world is having a meltdown(s). That's why I'm all about running large language models (LLMs) like Llama3 locally. Yep, right on your trusty MacBook. Sure, the cloud's got its perks, but here's why local is the way to go, especially for me: Privacy:  When you're brainstorming the next big thing, you don't want your ideas floating around on some random server. Keeping your data local means it's  yours , and that's a level of control I can get behind. Offline = Uninterrupted Flow:  Whether you're on a plane, at a coffee shop with spotty wifi, or jus...
Post a Comment
Read more