title: Error while using dataframe show method in pyspark
body: <p>I am trying to read data from BigQuery using pandas and pyspark. I am able to get the data but somehow getting below error while converting it into Spark DataFrame.</p>
  
  <pre><code>py4j.protocol.Py4JJavaError: An error occurred while calling o28.showString.
  : java.lang.IllegalStateException: Could not find TLS ALPN provider; no working netty-tcnative, Conscrypt, or Jetty NPN/ALPN available
      at com.google.cloud.spark.bigquery.repackaged.io.grpc.netty.shaded.io.grpc.netty.GrpcSslContexts.defaultSslProvider(GrpcSslContexts.java:258)
      at com.google.cloud.spark.bigquery.repackaged.io.grpc.netty.shaded.io.grpc.netty.GrpcSslContexts.configure(GrpcSslContexts.java:171)
      at com.google.cloud.spark.bigquery.repackaged.io.grpc.netty.shaded.io.grpc.netty.GrpcSslContexts.forClient(GrpcSslContexts.java:120)
      at com.google.cloud.spark.bigquery.repackaged.io.grpc.netty.shaded.io.grpc.netty.NettyChannelBuilder.buildTransportFactory(NettyChannelBuilder.java:401)
      at com.google.cloud.spark.bigquery.repackaged.io.grpc.internal.AbstractManagedChannelImplBuilder.build(AbstractManagedChannelImplBuilder.java:444)
      at com.google.cloud.spark.bigquery.repackaged.com.google.api.gax.grpc.InstantiatingGrpcChannelProvider.createSingleChannel(InstantiatingGrpcChannelProvider.java:223)
      at com.google.cloud.spark.bigquery.repackaged.com.google.api.gax.grpc.InstantiatingGrpcChannelProvider.createChannel(InstantiatingGrpcChannelProvider.java:169)
      at com.google.cloud.spark.bigquery.repackaged.com.google.api.gax.grpc.InstantiatingGrpcChannelProvider.getTransportChannel(InstantiatingGrpcChannelProvider.java:156)
      at com.google.cloud.spark.bigquery.repackaged.com.google.api.gax.rpc.ClientContext.create(ClientContext.java:157) 
  </code></pre>
  
  <p>Following is the environment detail </p>
  
  <pre><code>Python version : 3.7
  Spark version : 2.4.3
  Java version : 1.8
  </code></pre>
  
  <p>The code is as follow</p>
  
  <pre><code>import google.auth
  import pyspark
  from pyspark import SparkConf, SparkContext
  from pyspark.sql import SparkSession , SQLContext
  from google.cloud import bigquery
  
  
  # Currently this only supports queries which have at least 10 MB of results
  QUERY = """ SELECT * FROM test limit 1 """
  
  #spark = SparkSession.builder.appName('Query Results').getOrCreate()
  sc = pyspark.SparkContext()
  bq = bigquery.Client()
  
  print('Querying BigQuery')
  project_id = ''
  query_job = bq.query(QUERY,project=project_id)
  
  # Wait for query execution
  query_job.result()
  
  df = SQLContext(sc).read.format('bigquery') \
      .option('dataset', query_job.destination.dataset_id) \
      .option('table', query_job.destination.table_id)\
      .option("type", "direct")\
      .load()
  
  df.show()
  </code></pre>
  
  <p>I am looking some help to solve this issue.</p>