I'm using the spark elasticsearch connector and I want to extract from ES some fields plus the _id.
myquery = """{"query":..., """
val df = spark.read.format("org.elasticsearch.spark.sql")
                 .option("query", myquery)
                 .option("pushdown", "true")
                 .load("myindex/mytype")
                 .limit(10) 
                 .select("myfield","_id") 
Unfortunately, the _id field is not recognized:
AnalysisException: u'cannot resolve \'`_id`\' given input columns: 
[query, size, @version, @timestamp, 
 sourceinfo, signaletic, document, metadata, fields, aggs]
With this mapping I can select for example document.{fieldA}, sourceinfo.{fieldB}, etc. but not _id. It's like if it's at a level to high in the mapping.
Any idea how to get this particular field?
You can access _id or the metadata by setting the es.read.metadata to True
For example in your code:
myquery = """{"query":..., """
val df = spark.read.format("org.elasticsearch.spark.sql")
                 .option("query", myquery)
                 .option("pushdown", "true")
                 .option("es.read.metadata",True) # Set it to True
                 .load("myindex/mytype")
                 .limit(10) 
                 .select("myfield","_id") 
When you do
df.printSchema()
it will print something like ( in my case )
 |-- user_id: string (nullable = true)
 |-- user_rt: string (nullable = true)
 |-- user_rt_id: string (nullable = true)
 |-- username: string (nullable = true)
 |-- video: long (nullable = true)
 |-- _metadata: map (nullable = true) # this map column will be added
 |    |-- key: string
 |    |-- value: string (valueContainsNull = true)
You can further extract the properties like
_index, _type, _id, _score, sort from _metadata column
To access the _id column from _metadata (map type) i have used this, you can use what you think best
df.createOrReplaceTempView('temp_table_name')
spark.sql(""" 
     SELECT 
     _metadata._id as reference_id 
     FROM temp_table_name 
    """)
Hope this solves your problem
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