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Ambari Hadoop/Spark and Elasticsearch SSL Integration


Ambari Hadoop/Spark and Elasticsearch SSL Integration

By : Jake M.
Date : October 16 2020, 03:08 PM
should help you out For the project setup part of the question you can take a look at
https://github.com/zouzias/elasticsearch-spark-example
code :


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How do you read and write from/into different ElasticSearch clusters using spark and elasticsearch-hadoop?

How do you read and write from/into different ElasticSearch clusters using spark and elasticsearch-hadoop?


By : user3312446
Date : March 29 2020, 07:55 AM
around this issue Spark uses the hadoop-common library for file access, so whatever file systems Hadoop supports will work with Spark. I've used it with HDFS, S3 and GCS.
I'm not sure I understand why you don't just use elasticsearch-hadoop. You have two ES clusters, so you need to access them with different configurations. sc.newAPIHadoopFile and rdd.saveAsHadoopFile take hadoop.conf.Configuration arguments. So you can without any problems use two ES clusters with the same SparkContext.
How to reindex data from one Elasticsearch cluster to another with elasticsearch-hadoop in Spark

How to reindex data from one Elasticsearch cluster to another with elasticsearch-hadoop in Spark


By : abdAllah khaled
Date : March 29 2020, 07:55 AM
wish of those help You don't need to configure the node address inside the SparkConf for the matter.
When you use your DataFrameWriter with elasticsearch format, you can pass the node address as an option as followed :
code :
val df = sqlContext.read
                  .format("elasticsearch")
                  .option("es.nodes", "node1.cluster1:9200")
                  .load("your_index/your_type")

df.write
    .option("es.nodes", "node2.cluster2:9200")
    .save("your_new_index/your_new_type")
Ambari Hadoop Spark Cluster Firewall Issues

Ambari Hadoop Spark Cluster Firewall Issues


By : BornaGajic
Date : March 29 2020, 07:55 AM
Hope this helps Ok, so working with some folks on the Hortonworks community, I was was able to come up with a solution. Basically, you need to have at least one port defined, but you can extend that by specifying the spark.port.MaxRetries = xxxxx. By combining this setting along with the spark.driver.port = xxxxx, you can have a range starting at the spark.driver.port and ending with the spark.port.maxRetries.
If you use Ambari as your manager, the settings are under "Custom spark2-defaults" section (I assume under a fully open-source stack install, this would just be a setting under the normal Spark config):
Ambari-Update failed (Ambari 2.4 to 2.6) - Hadoop services won't start anymore

Ambari-Update failed (Ambari 2.4 to 2.6) - Hadoop services won't start anymore


By : Mohit Butola
Date : March 29 2020, 07:55 AM
Does that help Finally I was able to downgrade my Ambari installation back to version 2.4.2 as it was before starting the upgrade process.
To make a downgrade you have to do the following steps on the appropriate nodes:
code :
# delete the new ambari repo file
rm /etc/yum.repos.d/ambari.repo

# download the old ambari repo file (for me version 2.4.2), as described in ambari installation guide (here for Centos 7)
wget -nv http://public-repo-1.hortonworks.com/ambari/centos7/2.x/updates/2.4.2.0/ambari.repo -O /etc/yum.repos.d/ambari.repo

yum clean all
yum repolist
# check for the correct version (e.g. 2.4.2) of the Ambari repo

# Downgrade all components to this version
yum downgrade ambari-metrics-monitor
yum downgrade ambari-metrics-hadoop-sink
yum downgrade ambari-agent
...
Elasticsearch-hadoop & Elasticsearch-spark sql - Tracing of statements scan&scroll

Elasticsearch-hadoop & Elasticsearch-spark sql - Tracing of statements scan&scroll


By : Lester Paradero
Date : March 29 2020, 07:55 AM
I wish this help you
As far as I know it is an expected behavior. All sources I know behave exactly the same way and intuitively it make sense. SparkSQL is designed for analytical queries and it make more sense to fetch data, cache and process locally. See also Does spark predicate pushdown work with JDBC?
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