Merge pull request awslabs#182 from awslabs/copy-table

Copy table

tools/python/copy-table/README.md

@@ -37,7 +37,7 @@ Check the following guide to learn more: [Limits for UNLOAD from Timestream for
 Example to unload the Timestream table *myTable* in the database *sourcedb* to the folder *unload* in the *timestream-unload-sourcedb-mytable* S3 bucket.
 Also, it applies an S3 bucket policy to allow the IAM Role *BatchLoadRole* of account *123456789123* to allow the copy.  Does day level partitions.
  ```bash
-python3 unload.py -region eu-west-1 -s3_uri s3://timestream-unload-sourcedb-mytable/unload -database sourcedb -table myTable -iam_role_bucket_policy arn:aws:iam::123456789123:role/BatchLoadRole -p day
+python3.10 unload.py --region eu-west-1 --s3_uri s3://timestream-unload-sourcedb-mytable/unload --database sourcedb --table myTable --iam_role_bucket_policy arn:aws:iam::123456789123:role/BatchLoadRole --partition day
 ```
 
 ## Getting started with BATCH LOAD
@@ -85,15 +85,15 @@ Target bucket and error bucket names are given by *s3_target_bucket* and *s3_tar
 Destination prefix will be created with prefix dest/ given by *destination_s3_prefix*. Desired data model file is chosen as *data_model_sample.json* in the current location of the script. 
 
  ```bash
-python3 batch_load.py --region us-west-2 --create_timestream_resource --database=targetdb --table=myTable --partition_key city --copy_s3_bucket --s3_source_bucket_location  timestream-unload-sourcedb-mytable --source_s3_prefix unload/results/ --create_destination_bucket --s3_target_bucket timestream-batchload-targetdb-mytable --destination_s3_prefix dest/ --create_error_logging_bucket --s3_target_error_bucket timestream-batchload-error-logs --data_model_file "data_model_sample.json"      
+python3.10 batch_load.py --region us-west-2 --create_timestream_resource --database=targetdb --table=myTable --partition_key city --copy_s3_bucket --s3_source_bucket_location  timestream-unload-sourcedb-mytable --source_s3_prefix unload/results/ --create_destination_bucket --s3_target_bucket timestream-batchload-targetdb-mytable --destination_s3_prefix dest/ --create_error_logging_bucket --s3_target_error_bucket timestream-batchload-error-logs --data_model_file "data_model_sample.json"      
 ```
 
 **Without S3 Copy** 
 Example to execute a batch load to the target Timestream table *myTable* with partition key *city* in the database *targetdb* with  *eu-west-1* region.
 Timestream objects are created by this script as per *create_timestream_resource* parameter. Source data are located in the S3 bucket *timestream-unload-sourcedb-mytable* with prefix *unload/results/*.
 Error logs are stored into S3 bucket *timestream-batchload-error-logs*. If you need error log buckets to be created specify --create_error_logging_bucket.
  ```bash
-python3 batch_load.py --region eu-west-1 --database=targetdb --table=myTable  --s3_target_bucket timestream-unload-sourcedb-mytable --destination_s3_prefix unload/results/  --data_model_file "data_model_sample.json" --create_timestream_resource --partition_key city   --s3_target_error_bucket timestream-batchload-error-logs
+python3.10 batch_load.py --region eu-west-1 --database=targetdb --table=myTable  --s3_target_bucket timestream-unload-sourcedb-mytable --destination_s3_prefix unload/results/  --data_model_file "data_model_sample.json" --create_timestream_resource --partition_key city   --s3_target_error_bucket timestream-batchload-error-logs
 ```
 
 ## Usage and Requirements
@@ -102,7 +102,7 @@ These are the full steps to execute the script in your AWS Account.
 
 1. Log into your AWS account and select the AWS Region in which your Timestream table is stored
 
-2. Launch [AWS CloudShell](https://console.aws.amazon.com/cloudshell/home) or your local shell (Python 3.10 or newer is required)
+2. Launch [AWS CloudShell](https://console.aws.amazon.com/cloudshell/home) or your local shell (Python 3.10 or newer is **required**)
 
 3. Clone this source code project using [git](https://git-scm.com/) or download it manually