How To Push a Spark Dataframe to Elastic Search (Pyspark)

Question

Beginner ES Question here

What is the workflow or steps for pushing a Spark Dataframe to Elastic Search?

From research, I believe I need to use

Answer 1

Managed to find an answer so I'll share. Spark DF's (from pyspark.sql) don't currently support the newAPIHadoopFile() methods; however, df.rdd.saveAsNewAPIHadoopFile() was giving me errors as well. The trick was to convert the df to strings via the following function

def transform(doc):
    import json
    import hashlib

    _json = json.dumps(doc)
    keys = doc.keys()
    for key in keys:
        if doc[key] == 'null' or doc[key] == 'None':
            del doc[key]
    if not doc.has_key('id'):
        id = hashlib.sha224(_json).hexdigest()
        doc['id'] = id
    else:
        id = doc['id']
    _json = json.dumps(doc)
    return (id, _json)

So my JSON workflow is:

1: df = spark.read.json('XXX.json')

2: rdd_mapped = df.rdd.map(lambda y: y.asDict())

3: final_rdd = rdd_mapped.map(transform)

4:

final_rdd.saveAsNewAPIHadoopFile(
     path='-', 
     outputFormatClass="org.elasticsearch.hadoop.mr.EsOutputFormat",
     keyClass="org.apache.hadoop.io.NullWritable",  
     valueClass="org.elasticsearch.hadoop.mr.LinkedMapWritable", 
     conf={ "es.resource" : " / ", "es.mapping.id":"id", 
         "es.input.json": "true", "es.net.http.auth.user":"elastic",
         "es.write.operation":"index", "es.nodes.wan.only":"false",
         "es.net.http.auth.pass":"changeme", "es.nodes":", , ...",
         "es.port":"9200" })

More information on ES arguments can be found here (Scroll to 'Configuration')