title: Spark dynamic frame show method yields nothing
body: <p>So I am using AWS Glue auto-generated code to read csv file from S3 and write it to a table over a JDBC connection. Seems simple, Job runs successfully with no error but it writes nothing. When I checked the Glue Spark Dynamic Frame it does contents all the rows (using .count()). But when do a .show() on it yields nothing.</p>
  
  <p>.printSchema() works fine. Tried logging the error while using .show(), but no errors or nothing is printed. Converted the DynamicFrame to the data frame using .toDF and the show method it works. 
  I thought there is some problem with the file, trying to narrow to certain columns. But even with just 2 columns in the file same thing. Clearly marked string in double quotes, still no success.</p>
  
  <p>We have things like JDBC connection that needs to be picked from Glue configuration. Which I guess regular spark data frame can't do. Hence need dynamic frame working.</p>
  
  <pre><code>import sys
  from awsglue.transforms import *
  from awsglue.utils import getResolvedOptions
  from pyspark.context import SparkContext
  from awsglue.context import GlueContext
  from awsglue.job import Job
  from awsglue.dynamicframe import DynamicFrame
  import logging
  logger = logging.getLogger()
  logger.setLevel(logging.DEBUG)
  
  glueContext = GlueContext(SparkContext.getOrCreate())
  spark = glueContext.spark_session
  
  datasource0 = glueContext.create_dynamic_frame.from_options('s3', {'paths': ['s3://bucket/file.csv']}, 'csv', format_options={'withHeader': True,'skipFirst': True,'quoteChar':'"','escaper':'\\'})
  
  datasource0.printSchema()
  datasource0.show(5)
  </code></pre>
  
  <p>Output</p>
  
  <pre><code>root
  |-- ORDERID: string
  |-- EVENTTIMEUTC: string
  </code></pre>
  
  <p>Here is what the converting to regular data frame yields.</p>
  
  <pre><code>datasource0.toDF().show()
  </code></pre>
  
  <p>Output</p>
  
  <pre><code>+-------+-----------------+
  |ORDERID|     EVENTTIMEUTC|
  +-------+-----------------+
  |      2| "1/13/2018 7:50"|
  |      3| "1/13/2018 7:50"|
  |      4| "1/13/2018 7:50"|
  |      5| "1/13/2018 7:50"|
  |      6| "1/13/2018 8:52"|
  |      7| "1/13/2018 8:52"|
  |      8| "1/13/2018 8:53"|
  |      9| "1/13/2018 8:53"|
  |     10| "1/16/2018 1:33"|
  |     11| "1/16/2018 2:28"|
  |     12| "1/16/2018 2:37"|
  |     13| "1/17/2018 1:17"|
  |     14| "1/17/2018 2:23"|
  |     15| "1/17/2018 4:33"|
  |     16| "1/17/2018 6:28"|
  |     17| "1/17/2018 6:28"|
  |     18| "1/17/2018 6:36"|
  |     19| "1/17/2018 6:38"|
  |     20| "1/17/2018 7:26"|
  |     21| "1/17/2018 7:28"|
  +-------+-----------------+
  only showing top 20 rows
  </code></pre>
  
  <p>Here is the some data.</p>
  
  <pre><code>ORDERID, EVENTTIMEUTC
  1, "1/13/2018 7:10"
  2, "1/13/2018 7:50"
  3, "1/13/2018 7:50"
  4, "1/13/2018 7:50"
  5, "1/13/2018 7:50"
  6, "1/13/2018 8:52"
  7, "1/13/2018 8:52"
  8, "1/13/2018 8:53"
  9, "1/13/2018 8:53"
  10, "1/16/2018 1:33"
  11, "1/16/2018 2:28"
  12, "1/16/2018 2:37"
  13, "1/17/2018 1:17"
  14, "1/17/2018 2:23"
  15, "1/17/2018 4:33"
  16, "1/17/2018 6:28"
  17, "1/17/2018 6:28"
  18, "1/17/2018 6:36"
  19, "1/17/2018 6:38"
  20, "1/17/2018 7:26"
  21, "1/17/2018 7:28"
  22, "1/17/2018 7:29"
  23, "1/17/2018 7:46"
  24, "1/17/2018 7:51"
  25, "1/18/2018 2:22"
  26, "1/18/2018 5:48"
  27, "1/18/2018 5:50"
  28, "1/18/2018 5:50"
  29, "1/18/2018 5:51"
  30, "1/18/2018 5:53"
  100, "1/18/2018 10:32"
  101, "1/18/2018 10:33"
  102, "1/18/2018 10:33"
  103, "1/18/2018 10:42"
  104, "1/18/2018 10:59"
  105, "1/18/2018 11:16"
  </code></pre>