Xlang dataflow

README.md

@@ -249,34 +249,13 @@ list for currently supported runtime options.
 ### Cross-language example
 An example is showing simple usage of [cross-language](https://beam.apache.org/roadmap/portability/) by writing objects into Snowflake and reading them from Snowflake.
 
-Currently, cross-language is supporting only by [Apache Flink](https://flink.apache.org/) as a runner in a stable manner but plans are to support all runners. 
-For more information about cross-language please see [multi sdk efforts](https://beam.apache.org/roadmap/connectors-multi-sdk/) 
-and [Beam on top of Flink](https://flink.apache.org/ecosystem/2020/02/22/apache-beam-how-beam-runs-on-top-of-flink.html) articles. 
+For more information about cross-language please see [multi sdk efforts](https://beam.apache.org/roadmap/connectors-multi-sdk/).
 
 #### Extra setup: 
-Please see [Apache Beam with Flink runner](https://beam.apache.org/documentation/runners/flink/)  for a setup. The specific setup for current version of snowflake is following:
-1. Setup a Flink cluster by following the Flink [Setup Quickstart](https://ci.apache.org/projects/flink/flink-docs-release-1.10/getting-started/tutorials/local_setup.html)
-or [Setting up Apache Flink on Mac OS X](https://streambench.wordpress.com/2017/10/26/setting-up-apache-flink-on-mac-os-x/) 
-2. Download Job server image:
+1. Follow steps form previous section `Setup required by all examples`
+1. Download and install Apache Beam Python SDK
 ```
-docker pull gcr.io/snowflake-poli/apachebeam_flink1.10_job_server:snowflake
-```
-3. Download Apache Beam Java SDK image:
-```
-docker pull gcr.io/snowflake-poli/apachebeam_java_sdk:2.20.0.dev
-```
-4. Change tag of downloaded Java SDK image to make the whole setup work:
-```
-docker tag gcr.io/snowflake-poli/apachebeam_java_sdk:2.20.0.dev apache/beam_java_sdk:2.20.0.dev
-```
-5. Start Job server:
-```
-docker run -p 8099:8099 -p 8098:8098 -p 8097:8097 gcr.io/snowflake-poli/apachebeam_flink1.10_job_server:snowflake
-```
-6. Download [Apache Beam Python SDK](https://storage.cloud.google.com/snowflake_artifacts/apachebeam_snowflake.whl?_ga=2.54472813.-471657054.1583857613).
-7. Install python Apache Beam Python SDK using Python 2.7
-```  
-python -m pip install apachebeam_snowflake.whl 
+    pip install apache-beam
 ```
 
 #### Executing:
@@ -288,16 +267,18 @@ python -m pip install apachebeam_snowflake.whl
    SCHEMA = <SNOWFLAKE SCHEMA>
    DATABASE = <SNOWFLAKE DATABASE>
    STAGING_BUCKET_NAME = <SNOWFLAKE STORAGE INTEGRATION NAME>
-   STORAGE_INTEGRATION = <SNOWFLAKE STORAGE INTEGRATION NAME> 
+   STORAGE_INTEGRATION_NAME = <SNOWFLAKE STORAGE INTEGRATION NAME> 
    TABLE = <SNOWFLAKE TABLE NAME> 
+
+   OPTIONS =[
+       "--runner=DataflowRunner",
+       "--project=<GCP PROJECT ID>",
+       "--staging_location=gs://<BUCKET NAME>/tmp/",
+       "--region=<REGION>",
+       "--temp_location=gs://<BUCKET NAME>/tmp/"
+   ]
     ``` 
 2. Run xlang_example.py:
     ```
     python xlang_example.py 
     ```
-2. [Go to Flink console](http://localhost:8081/)
-    ![Xlang Flink result](./images/xlang_flink_result.png)
-3. Go to GCS bucket to check saved files:
-    ![Xlang GCS result](./images/xlang_gcs_result.png)
-4. Check console
-    ![Xlang console result](./images/xlang_console_result.png)

xlang_example.py

@@ -2,6 +2,7 @@
 from apache_beam.options.pipeline_options import PipelineOptions
 from apache_beam.io.external.generate_sequence import GenerateSequence
 from apache_beam.io.external.snowflake import ReadFromSnowflake, WriteToSnowflake
+import logging
 
 SERVER_NAME = <SNOWFLAKE SERVER NAME>
 USERNAME = <SNOWFLAKE USERNAME>
@@ -11,7 +12,6 @@
 STAGING_BUCKET_NAME = <SNOWFLAKE STORAGE INTEGRATION NAME>
 STORAGE_INTEGRATION = <SNOWFLAKE STORAGE INTEGRATION NAME>
 TABLE = <SNOWFLAKE TABLE NAME>
-EXPANSION_SERVICE = 'localhost:8097'
 SCHEMA_STRING = """
 {"schema":[
     {"dataType":{"type":"text","length":null},"name":"text_column","nullable":true},
@@ -21,10 +21,11 @@
 """
 
 OPTIONS =[
-    "--runner=FlinkRunner",
-    "--flink_version=1.10",
-    "--flink_master=localhost:8081",
-    "--environment_type=LOOPBACK"
+    "--runner=DataflowRunner",
+    "--project=<GCP PROJECT ID>",
+    "--staging_location=gs://<BUCKET NAME>/tmp/",
+    "--region=<REGION>",
+    "--temp_location=gs://<BUCKET NAME>/tmp/"
 ]
 
 class Row(object):
@@ -50,7 +51,7 @@ def user_data_mapper(test_row):
 
     p = beam.Pipeline(options=PipelineOptions(OPTIONS))
     (p
-     | GenerateSequence(start=1, stop=3, expansion_service=EXPANSION_SERVICE)
+     | GenerateSequence(start=1, stop=3)
      | beam.Map(lambda num: Row("test" + str(num), num, True))
      | "Writing into Snowflake" >> WriteToSnowflake(
                 server_name=SERVER_NAME,
@@ -65,8 +66,7 @@ def user_data_mapper(test_row):
                 table_schema=SCHEMA_STRING,
                 user_data_mapper=user_data_mapper,
                 table=TABLE,
-                query=None,
-                expansion_service=EXPANSION_SERVICE)
+                query=None)
      )
     result = p.run()
     result.wait_until_finish()
@@ -91,18 +91,20 @@ def print_row(row):
                 schema=SCHEMA,
                 database=DATABASE,
                 staging_bucket_name=STAGING_BUCKET_NAME,
-                storage_integration=STORAGE_INTEGRATION,
+                storage_integration_name=STORAGE_INTEGRATION,
                 csv_mapper=csv_mapper,
-                table=TABLE,
-                expansion_service=EXPANSION_SERVICE)
+                table=TABLE)
      | "Print" >> beam.Map(print_row)
      )
     result = p.run()
     result.wait_until_finish()
 
+
 def run():
-    run_write()
+    # run_write()
     run_read()
 
+
 if __name__ == '__main__':
+    logging.getLogger().setLevel(logging.INFO)
     run()