I am a starter in hadoop. How do I know how much RAM does my hadoop cluster have and how much RAM is my application using? I am using CDH 5.3 version but I would prefer knowing it in general for hadoop clusters.
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Does anyone know which containers technology (Docker, LXC,....) is used in apache Hadoop, especially in (HDFS) and (Mapreduce)?
I know its used container technology but I can not find which one in specific.
Out of the box, none. What YARN calls "containers", by default, are bare-metal JVM instances that are scheduled using the YARN NodeManagers.
YARN can be configured to use Docker or runC.
I am trying to follow the Apache documentation in order to integrate Prometheus with Apache Hadoop. One of the preliminary steps is to setup Apache Ozone cluster. However, I am finding issues in running the ozone cluster concurrently with Hadoop. It throws a class not found exception for "org.apache.hadoop.ozone.HddsDatanodeService" whenever I try to start the ozone manager or storage container manager.
I also found that ozone 1.0 release is pretty recent and it is mentioned that it is tested with Hadoop 3.1. I have a running Hadoop cluster of version of 3.3.0. Now, I doubt if the version is a problem.
The tar ball for Ozone also has the Hadoop config files, but I wanted to configure ozone with my existing Hadoop cluster. I want to configure the ozone with my existing hadoop cluster.
Please let me know what should be the right approach here. If this can not be done, then please also let me know what is good way to monitor and extract metrics for Apache Hadoop in production.
Does anyone has worked on this configuration: Apache Hive on Apache Spark?
What is the latest version compatibility for this configuration?
I want to implement this in my production systems. Kindly help with the compatibility matrix for Apache Hadoop, Apache Hive, Apache Spark and Apache Zeppelin.
You have to use hive2 (0.11+) and SPARK 2.2.0 and in hive-site.xml. And you have to set Spark as executor engine so you can easily run your queries on top of Spark.
In hive2 there are some options like Tez, llap etc. For more information kindly check the document Hive on Spark: Getting Started.
follow the tutorial
apache hive installation
and then just copy the hive-site.xml to $APACHE_HOME/conf
Hive is moving to rely only on the Tez execution engine. Please build all new workloads on MapReduce or Tez.
I am a newbie to Hadoop, I am trying to learn it and came across 2 versions of InputFormat.
org/apache/hadoop/mapred/InputFormat
org/apache/hadoop/mapreduce/InputFormat
The explanation of both apis seems to be same but one is interface and other is a class. Can someone please help me why there are 2 APIs with same explanation in Hadoop?
MapReduce has undergone a complete overhaul in hadoop-0.23 and it is called as MapReduce 2.0 (MRv2) or YARN.
org/apache/hadoop/mapred/InputFormat refers to hadoop MRV1
org/apache/hadoop/mapreduce/InputFormat refers to hadoop MRV2
Both these libraries refer to same functionality.
MRV2 is a rewrite of MRV1 for the compatibility of YARN architecture.
I am new to Cassandra and Hadoop. I am trying to read cassandra data on hourly basis and dump into HDFS. Cassandra and Hadoop are on different clusters. Any pointers on Clients/API I could use to do this is much appreciated.
I recommend Java because Hadoop and Cassandra are both Java based. Astyanax is a good Java Cassandra API.
I've used org.apache.hadoop to write to HDFS using Java but there might be something better out there.