class_docstr: Write documents to mongoDB.
  
  The writer can be used to store documents in mongoDB while dealing with tensorflow
  based models and inference outputs. Without loss of generality, consider an ML
  model that is being used for inference. The outputs of inference can be modelled into
  a structured record by enriching the schema with additional information( for ex: metadata
  about input data and the semantics of the inference etc.) and can be stored in mongo
  collections for persistence or future analysis.
  
  To make a connection and write the documents to the mongo collections,
  the `tfio.experimental.mongodb.MongoDBWriter` API can be used.
  
  Example:
  
  >>> URI = "mongodb://mongoadmin:default_password@localhost:27017"
  >>> DATABASE = "tfiodb"
  >>> COLLECTION = "test"
  >>> writer = tfio.experimental.mongodb.MongoDBWriter(
      uri=URI, database=DATABASE, collection=COLLECTION
  )
  >>> for i in range(1000):
  ...    data = {"key{}".format(i): "value{}".format(i)}
  ...    writer.write(data)
docstr: Delete all matching documents
docstr_tok: ["Delete","all","matching","documents"]
code: def _delete_many(self, doc):
      """Delete all matching documents"""
  
      core_ops.io_mongo_db_writable_delete_many(
          resource=self.resource, record=json.dumps(doc)
      )
  
file_path: io/tensorflow_io/python/experimental/mongodb_writer_ops.py
imports: import json
  from urllib.parse import urlparse
  import tensorflow
  from tensorflow_io.python.ops import core_ops
  from tensorflow_io.python.experimental import serialization_ops
label_desc: Use image node_id 3 for calling the MongoDBWriter obj's underlying member method code with example usage: obj._delete_many(doc) without return types