Python is very rich with data analytics libraries which brought me to use it for one of the use case. The same use case initially I tried to perform with Java also, but I found that the effort is more in java side. So just for the POC purpose, I choose python.

My sue case was to read and query on parquet file content without downloading it.

So to perform this activity, I converted the parquet file to streams with the help of BytesIO.

Once, I got the stream, I used pyArrow library which helped me to read this data into python data frames directly. 

blob_service_client_instance = createBlobServiceClient()

    blob_client_instance = blob_service_client_instance.get_blob_client(

    CONTAINER_NAME, 'userdata1.parquet', snapshot=None)

    blob_data = blob_client_instance.download_blob()

    stream = BytesIO()

    blob_data.readinto(stream)

    processed_df = pd.read_parquet(stream, engine='pyarrow')

    # print(processed_df.columns)

    return processed_df 

Once you have the data inside the dataframe, you can put query into it easily.

 processed_df = donwloadParquetFile()

    setDisplayForDataFrame(None,None,1000)

    print(processed_df)

    print (processed_df.head(3))

    print("---------------------Query Output--------------------------------")

    print(processed_df.query(query))

And this query will be your query.

In my case, I was passing it from my main method, which was int he form of : 

first_name == "Amanda" and last_name == "Jordan"

To show the results in console, we can set the option in panda dataframe.