updated README.md

Author: HariSekhon

README.md

@@ -69,7 +69,7 @@ Environment variables are supported for convenience and also to hide credentials
 - ```pig-text-to-elasticsearch.pig``` / ```pig-text-to-solr.pig``` - [Pig](https://pig.apache.org/) scripts to bulk index unstructured files in [Hadoop](http://hadoop.apache.org/) to [Elasticsearch](https://www.elastic.co/products/elasticsearch) or [Solr](http://lucene.apache.org/solr/) / [SolrCloud clusters](https://wiki.apache.org/solr/SolrCloud)
 - ```pig_udfs.jy``` - Pig Jython UDFs for Hadoop
 - ```ipython-notebook-pyspark.py``` - per-user authenticated IPython Notebook + PySpark integration to allow each user to auto-create their own password protected IPython Notebook running Spark
-- ```json_docs_to_bulk_multiline.py``` - converts json files to bulk multi-record one-line-per-json-document format for pre-processing and loading to big data systems like Hadoop and MongoDB, can recurse directory trees, and mix json-doc-per-file / bulk-multiline-json / directories / standard input, combines all json documents and outputs bulk-one-json-document-per-line to standard output for convenient command line chaining and redirection, optionally continues on error, collects broken records to standard error for logging and later reprocessing for bulk batch jobs, even supports single quoted json while not technically valid json is used by MongoDB and even handles embedded double quotes in 'single quoted json'
+- ```json_docs_to_bulk_multiline.py``` - converts json files to bulk multi-record one-line-per-json-document format for pre-processing and loading to big data systems like [Hadoop](http://hadoop.apache.org/) and [MongoDB](https://www.mongodb.com/), can recurse directory trees, and mix json-doc-per-file / bulk-multiline-json / directories / standard input, combines all json documents and outputs bulk-one-json-document-per-line to standard output for convenient command line chaining and redirection, optionally continues on error, collects broken records to standard error for logging and later reprocessing for bulk batch jobs, even supports single quoted json while not technically valid json is used by MongoDB and even handles embedded double quotes in 'single quoted json'
 - ```json_to_xml.py``` - JSON to XML converter
 - ```xml_to_json.py``` - XML to JSON converter
 - ```spark_avro_to_parquet.py``` - PySpark Avro => Parquet converter