elasticsearch-hadoop | elasticsearch-hadoop connector for elassandra
kandi X-RAY | elasticsearch-hadoop Summary
kandi X-RAY | elasticsearch-hadoop Summary
This is a modified version of the Eleasticsearch-hadoop connector for Elassandra. See Elassandra documentation for more information. Elasticsearch real-time search and analytics natively integrated with Hadoop. Supports Map/Reduce, Cascading, Apache Hive, Apache Pig, Apache Spark and Apache Storm. See project page and documentation for detailed information.
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Top functions reviewed by kandi - BETA
- Reads the hit as a map .
- Initialize the extractors .
- Assemble the query parameters .
- Sets the proxy settings
- Returns the Levenshtein distance between two strings .
- Writes a tuple to the generator .
- Creates a reader for a partition .
- Returns an array size over the given minimum and maximum size .
- Find a matching object .
- Extract field projection from UDF configuration .
elasticsearch-hadoop Key Features
elasticsearch-hadoop Examples and Code Snippets
Lines of Code : 16License : Permissive (Apache-2.0)
CopyLicensed to Elasticsearch under one or more contributor
license agreements. See the NOTICE file distributed with
this work for additional information regarding copyright
ownership. Elasticsearch licenses this file to you under
the Apache License, Ver
com.strapdata..elasticsearch
elasticsearch-hadoop
5.5.1.BUILD-SNAPSHOT
sonatype-oss
http://oss.sonatype.org/content/repositories/snapshots
true
CREATE EXTERNAL TABLE artists (
id BIGINT,
name STRING,
links STRUCT)
STORED BY 'org.elasticsearch.hadoop.hive.EsStorageHandler'
TBLPROPERTIES('es.resource' = 'radio/artists');
INSERT OVERWRITE TABLE artists
SELECT NULL, s Community Discussions
Trending Discussions on elasticsearch-hadoop
QUESTION
While using elasticsearch-hadoop library for reading elasticsearch index with empty attribute, getting the exception
...ANSWER
Answered 2021-Apr-30 at 05:45It worked by setting elasticsearch-hadoop property es.field.read.empty.as.null = no
QUESTION
I'm getting invalid timestamp when reading Elasticsearch records using Spark with elasticsearch-hadoop library. I'm using following Spark code for records reading:
...ANSWER
Answered 2021-Jan-25 at 19:34Problem was with the data in ElasticSearch. start_time field was mapped as epoch_seconds and contained value epoch seconds with three decimal places (eg 1611583978.684). Everything works fine after we have converted epoch time to millis without any decimal places
QUESTION
I'm new to Kafka and pyspark. What I'm trying to do is publish some data into the Kafka and then using the pyspark-notebook to reach those data for further processing. I'm using Kafka and pyspark-notebook on docker and my spark version there is 2.4.4. to set up the environment and reaching data I'm running the following code:
...ANSWER
Answered 2020-Oct-23 at 19:48I found what was the problem. I need to add "kafka-client" jar file as well in my packages directory.
QUESTION
I had some problems using the Elasticsearch connector for Spark described here: https://www.elastic.co/guide/en/elasticsearch/hadoop/master/spark.html. I could not even get the examples on their page working with a plain vanilla instance of Elasticsearch 7.4.0 that I downloaded and started via
...ANSWER
Answered 2020-Oct-14 at 10:10You need to configure elasticsearch port and ip where its running please find the below i think this will help you.
QUESTION
Im working on a code in which i'm trying to stream data into elastic search using structured streaming by pySpark.
Spark version : 3.0.0 Installed Mode : pip
...ANSWER
Answered 2020-Aug-29 at 15:52Thank you so much, i was using spark 3 which is built on scala 2.12, unfortunately elasticsearch-hadoop jar is supported till 2.11 version of scala. I have downgraded my spark version to 2.4.6 which is built on scala 2.11.
QUESTION
I am trying to send sparkdataframe to Elasticsearch cluster. I have Spark dataframe(df).
I created index = "spark" but, when I ran this command:
...ANSWER
Answered 2020-May-20 at 08:00I believe you should to specify es.resource on write, format can be specified as es. The below worked for me on Spark 2.4.5 (running on docker) and ES version 7.5.1. First of all, make sure you're running pyspark with the following package:
QUESTION
My goal is to use the elasticsearch-hadoop connector to load data directly into ES with pySpark. I'm quite new to dataproc and pySpark and got stuck quite early.
I run a single node cluster (Image 1.3 ,Debian 9,Hadoop 2.9,Spark 2.3) and this my code. I assume I need to install Java.
Thanks!
...ANSWER
Answered 2020-Apr-23 at 17:51Ok, solved, I needed to stop the current context before I create my new SparkContext.
sc.stop()
QUESTION
With the Elasticsearch-hadoop Connector, is it possible to use the scripted_upsert to true on an upsert insertion ?
I am using the es.update.script.inline configuration, but i can't find any way to use the script_upsert to true and to empty the contents of the upsert
...ANSWER
Answered 2020-Mar-23 at 15:46I have found this issue : https://github.com/elastic/elasticsearch-hadoop/issues/538 on the project
It says
Scripted Upsert is unfortunately not supported at the moment
This was posted 2020/03/18
So for the moment, there is not the functionality
QUESTION
I came across this page, which has this code line :
...ANSWER
Answered 2020-Mar-01 at 12:50There are two aspects in the below code:
QUESTION
How to setup spark for speed?
I'm running spark-elasticsearch to analyze log data.
It takes about 5min to do aggregate/join with 2million rows (4gig).
I'm running 1 master, 3 workers on 3 machines. I increased executor memory to 8g, increased ES nodes from 1 to 3.
I'm running standalone clusters in client mode (https://becominghuman.ai/real-world-python-workloads-on-spark-standalone-clusters-2246346c7040) I'm not using spark-submit, just running python code after launching master/workers
Spark seems to launch 3 executors total (which are from 3 workers).
I'd like to tune spark a little bit to get the most performance with little tuning..
Which way should I take for optimization?
- consider other cluster (yarn, etc .. although I have no idea what they offer, but it seems it's easier to change memory related settings there)
- run more executors
- analyze the job plan with
explainapi- accept it takes that much time because you have to download 4gig data (should spark grap all data to run aggregate? such as group by and sum), if applicable, save the data to parquet (?) for further analysis
Below are my performance related setting
...ANSWER
Answered 2020-Jan-04 at 13:02It is not always a matter of memory or cluster configuration, I would suggest starting by trying to optimize the query/aggregation you're running before increasing memory.
You can find here some hints for Spark Performance Tuning. See also Tuning Spark. Make sure the query is optimal and avoid known bad performance as UDFs.
For executor and memory configuration in your cluster, you have to take into consideration the available memory and cores on all machines to calculate the adequate parameters. Here is an intersting post on best practices.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install elasticsearch-hadoop
You can use elasticsearch-hadoop like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the elasticsearch-hadoop component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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