S3 Access From Sagemaker Duckdb Slower Than Expected Threading

Unusually Slow Queries On Parquet Files In S3 Https Issue 6199 I did a quick check with some data i had on s3 but there is a clear speedup there when using a different numbers of threads cpus. i will use your scripts later today to see if i can reproduce the behaviour and figure out whats happening. Running a query directly from lambda should be considerably faster as long as you're in the same region as time to access should be much less. now if you're looking for a lot of specific info and doing something crazy like select * from said parquet files, it's not going to be good.

Error Unable To Connect When Querying S3 Issue 2123 Duckdb If you find that your workload in duckdb is slow, we recommend performing the following checks. more detailed instructions are linked for each point. do you have enough memory? duckdb works best if you have 1 4 gb memory per thread. are you using a fast disk?. I receive 1000s of parquet files with same schema every day into a s3 bucket. i am using duckdb with python3 extension to read all the parquet files to subset data from them. Newer versions of duckdb have made it really simple to authenticate with cloud storage services. in my case, i have already installed and configured my aws profile, and the snippet below will tell duckdb to use that configuration when making calls to s3. I am running my code on sagemaker, which runs my code slowly for the first time, but runs with proper speed, the second time around (i guess there's something getting stored in the cache).

Duckdb 10 Times Slower Than Sqlite Processing Time Series Duckdb Newer versions of duckdb have made it really simple to authenticate with cloud storage services. in my case, i have already installed and configured my aws profile, and the snippet below will tell duckdb to use that configuration when making calls to s3. I am running my code on sagemaker, which runs my code slowly for the first time, but runs with proper speed, the second time around (i guess there's something getting stored in the cache). All my testing seems to indicate that when reading from s3, duckdb never uses more than 2 threads, regardless of number of processors available. others have confirmed that this behavior is not expected. How can modern data teams achieve massive scalability, flexibility, and efficiency while avoiding the pitfalls of fragmented data lakes? this session explores taktile's journey from a complex mix of s3, glue, and snowflake to a fully integrated, pythonic lakehouse with apache iceberg, polaris catalog, and dlt. My customer's 220 gb of training data took 54 minutes for sagemaker to download. this is a rate of only 70 mb s, which is unexpectedly slow. he is accessing the data in s3 from his p3.8xlarge instance through a private vpc endpoint, so the theoretical maximum bandwidth is 25 gbps. is there anything that can be done to speed up the download?. Streamlining access to tabular datasets stored in amazon s3 tables with duckdb | aws storage blog as businesses continue to rely on data driven decision making, there’s an increasing demand for tools that streamline and accelerate the process of data analysis.

S3 Access From Sagemaker Duckdb Slower Than Expected Threading All my testing seems to indicate that when reading from s3, duckdb never uses more than 2 threads, regardless of number of processors available. others have confirmed that this behavior is not expected. How can modern data teams achieve massive scalability, flexibility, and efficiency while avoiding the pitfalls of fragmented data lakes? this session explores taktile's journey from a complex mix of s3, glue, and snowflake to a fully integrated, pythonic lakehouse with apache iceberg, polaris catalog, and dlt. My customer's 220 gb of training data took 54 minutes for sagemaker to download. this is a rate of only 70 mb s, which is unexpectedly slow. he is accessing the data in s3 from his p3.8xlarge instance through a private vpc endpoint, so the theoretical maximum bandwidth is 25 gbps. is there anything that can be done to speed up the download?. Streamlining access to tabular datasets stored in amazon s3 tables with duckdb | aws storage blog as businesses continue to rely on data driven decision making, there’s an increasing demand for tools that streamline and accelerate the process of data analysis.