amazon-timestream-tools
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awslabs
Related to recent PR - Amazon timestream in PHP example app : https://github.com/awslabs/amazon-timestream-tools/pull/161 Steps to reproduce: 1/ Create a Github code space environment from this repo 2/ run the following...
The Flink Connector does not seem to be compatible with Flink 1.15.2 (the Flink version now supported by Amazon Kinesis Data Analytics). When initialising the sink it throws the following...
1/ Add Scheduled query & multi-measure record sample for supported languages to https://github.com/awslabs/amazon-timestream-tools/blob/mainline/sample_apps. ( Note refer the sample code added in folder - https://github.com/awslabs/amazon-timestream-tools/tree/mainline/sample_apps_reinvent2021 ) 2/ Remove the redundant folder...
Requesting to add code sample to https://github.com/awslabs/amazon-timestream-tools/tree/mainline/integrations that runs a query using Timestream ODBC driver https://github.com/awslabs/amazon-timestream-odbc-driver
We are experiencing our production issue while writing data into Timestream database from Kinesis Data Analytics app in Tokyo Region. Our POC environment in Sydney region works fine. ~6894 records...
1. This code in the ipynb throws a syntax error: ``` query = """ DESCRIBE {}.{} """.format(DB_NAME, TABLE_NAME) ``` it should be ``` query = """ DESCRIBE "{}"."{}" """.format(DB_NAME, TABLE_NAME)...
I'm trying to write a PyFlink application with a kinesis stream as the source and timestream as the sink and I'm struggling to find any documentation or examples of how...
say 2 concurrent requests happen at the same time and each performs insert to timestream db. Each insert with identical: 1. measure value 2. measure name 3. time (timestamp) but...
Hi Team, we are trying to implement AWS Timestream for persisting our timeseries data. We have 4 years of historical data and our memory retention policy is 5 days. We...
Hi, team! We are developing with TimeStream where we query data from Timestream and encapsulate the data to return to the client. But now it is a little bit inconvenient...
