Issue with the Snappy package when trying to install an Hadoop DataNode using Apache Ambari

During an Hadoop cluster installation on Red Hat/CentOS using Apache Ambari (https://ambari.apache.org/), a DataNode could fail to install with the following error:

resource_management.core.exceptions.Fail: Execution of '/usr/bin/yum -d 0 -e 0 -y install snappy-devel' returned 1. Error: Package: snappy-devel-1.0.5-1.el6.x86_64 (HDP-UTILS-1.1.0.20)
           Requires: snappy(x86-64) = 1.0.5-1.el6
           Installed: snappy-1.1.0-1.el6.x86_64 (@ftp3-updates)
               snappy(x86-64) = 1.1.0-1.el6
           Available: snappy-1.0.5-1.el6.x86_64 (HDP-UTILS-1.1.0.20)
               snappy(x86-64) = 1.0.5-1.el6
You could try using --skip-broken to work around the problem
You could try running: rpm -Va --nofiles --nodigest

The root cause here is the following: Hadoop requires a version of the snappy-devel package that is a lower one of that already present on the machine. In order to fix the problem you have to connect to the host and execute the following commands from a shell:

yum remove snappy
yum install snappy-devel

and then retry the installation. It could have been nicer to have this error managed by the Ambari Python script itself rather than requiring a manual intervention. This issue has been reported for Ambari 2.1.0, but it is still present in the latest (2.2.0).

Comments

Exporting InfluxDB data to a CVS file

Sometimes you would need to export a sample of the data from an InfluxDB table to a CSV file (for example to allow a data scientist to do some offline analysis using a tool like Jupyter, Zeppelin or Spark Notebook). It is possible to perform this operation through the influx command line client. This is the general syntax: sudo /usr/bin/influx -database '<database_name>' -host '<hostname>' -username '<username>' -password '<password>' -execute 'select_statement' -format '<format>' > <file_path>/<file_name>.csv where the format could be csv , json or column . Example: sudo /usr/bin/influx -database 'telegraf' -host 'localhost' -username 'admin' -password '123456789' -execute 'select * from mem' -format 'csv' > /home/googlielmo/influxdb-export/mem-export.csv

Using Rapids cuDF in a Colab notebook

During last Spark+AI Summit Europe 2019 I had a chance to attend a talk from Miguel Martinez who was presenting Rapids , the new Open Source framework from NVIDIA for GPU accelerated end-to-end Data Science and Analytics. Fig. 1 - Overview of the Rapids eco-system Rapids is a suite of Open Source libraries: cuDF cuML cuGraph cuXFilter I enjoied the presentation and liked the idea of this initiative, so I wanted to start playing with the Rapids libraries in Python on Colab , starting from cuDF, but the first attempt came with an issue that I eventually solved. So in this post I am going to share how I fixed it, with the hope it would be useful to someone else running into the same blocker. I am assuming here you are already familiar with Google Colab. I am using Python 3.x as Python 2 isn't supported by Rapids. Once you have created a new notebook in Colab, you need to check if the runtime for it is set to use Python 3 and uses a GPU as hardware accelerator. You

Load testing MongoDB using JMeter

Apache JMeter ( http://jmeter.apache.org/ ) added support for MongoDB since its 2.10 release. In this post I am referring to the latest JMeter release (2.13). A preliminary JMeter setup is needed before starting your first test plan for MongoDB. It uses Groovy as scripting reference language, so Groovy needs to be set up for our favorite load testing tool. Follow these steps to complete the set up: Download Groovy from the official website ( http://www.groovy-lang.org/download.html ). In this post I am referring to the Groovy release 2.4.4, but using later versions is fine. Copy the groovy-all-2.4.4.jar to the $JMETER_HOME/lib folder. Restart JMeter if it was running while adding the Groovy JAR file. Now you can start creating a test plan for MongoDB load testing. From the UI select the MongoDB template ( File -> Templates... ). The new test plan has a MongoDB Source Config element. Here you have to setup the connection details for the database to be tested: The Threa

Googlielmo's blog

Search This Blog