How to query an Elasticsearch index using Pyspark and Dataframes

Below is how I do it.

General environment settings and command:

export SPARK_HOME=/home/ezerkar/spark-1.6.0-bin-hadoop2.6export PYSPARK_DRIVER_PYTHON=ipython2./spark-1.6.0-bin-hadoop2.6/bin/pyspark --driver-class-path=/home/eyald/spark-1.6.0-bin-hadoop2.6/lib/elasticsearch-hadoop-2.3.1.jar

Code:

from pyspark import SparkConffrom pyspark.sql import SQLContextconf = SparkConf().setAppName("ESTest")sc = SparkContext(conf=conf)sqlContext = SQLContext(sc)q ="""{  "query": {    "filtered": {      "filter": {        "exists": {          "field": "label"        }      },      "query": {        "match_all": {}      }    }  }}"""es_read_conf = {    "es.nodes" : "localhost",    "es.port" : "9200",    "es.resource" : "titanic/passenger",    "es.query" : q}es_rdd = sc.newAPIHadoopRDD(    inputFormatClass="org.elasticsearch.hadoop.mr.EsInputFormat",    keyClass="org.apache.hadoop.io.NullWritable",     valueClass="org.elasticsearch.hadoop.mr.LinkedMapWritable",     conf=es_read_conf)sqlContext.createDataFrame(es_rdd).collect()

You can also define data-frame columns. Refer Here for more info.

Hope that it helps!

I am running my code in a EMR cluster from Amazon using pyspark. Then, the way I made it work was following these steps:

1) Put this bootstrap action in the cluster creation (to create localhost elasticsearch server):

s3://awssupportdatasvcs.com/bootstrap-actions/elasticsearch/elasticsearch_install.4.0.0.rb

2) I run these commands to populate the elasticsearch database with some data:

 curl -XPUT "http://localhost:9200/movies/movie/1" -d' {   "title": "The Godfather",   "director": "Francis Ford Coppola",   "year": 1972  }'

You can also run other curl commands if you wish, like:

curl -XGET http://localhost:9200/_search?pretty=true&q={'matchAll':{''}}

3) I inited pyspark using the following parameters:

pyspark --driver-memory 5G --executor-memory 10G --executor-cores 2 --jars=elasticsearch-hadoop-5.5.1.jar

I had downloaded the elasticsearch python client previously

4) I run the following code:

from pyspark import SparkConffrom pyspark.sql import SQLContextq ="""{  "query": {    "match_all": {}  }  }"""es_read_conf = {    "es.nodes" : "localhost",    "es.port" : "9200",    "es.resource" : "movies/movie",    "es.query" : q}es_rdd = sc.newAPIHadoopRDD(    inputFormatClass="org.elasticsearch.hadoop.mr.EsInputFormat",    keyClass="org.apache.hadoop.io.NullWritable",     valueClass="org.elasticsearch.hadoop.mr.LinkedMapWritable",     conf=es_read_conf)sqlContext.createDataFrame(es_rdd).collect()

Then I finally got successful result from the command.

I have faced a issue similar to this to get geo-filtered data into a PySpark DataFrame. I am using elasticsearch-spark-20_2.11-5.2.2.jar with Spark version 2.1.1 and ES version 5.2. I was able to load the data into a DataFrame by specifying my query as an option while creating the DataFrame

My geo-query

q ="""{  "query": {        "bool" : {            "must" : {                "match_all" : {}            },           "filter" : {                "geo_distance" : {                    "distance" : "100km",                    "location" : {                        "lat" : 35.825,                        "lon" : -87.99                    }                }            }        }    }}"""

I used the following command to load data into DataFrame

spark_df = spark.read.format("es").option("es.query", q).load("index_name")