Probabilistic guarantees for SQL query executionData manipulation in SQLHow do I write a SQL (or dwSQL) query across these two different datasets?Sql satament sql serverSpark SQL Pivot CrossTab functionalitySQL Server and skip first n rowsData dashboard for SQL server databaseNot enough replicas available for query at consistency all (2 required but only 1 alive)Natural Language to SQL queryCall a SQL procedure, for each group byPython-SQL database
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Probabilistic guarantees for SQL query execution
Data manipulation in SQLHow do I write a SQL (or dwSQL) query across these two different datasets?Sql satament sql serverSpark SQL Pivot CrossTab functionalitySQL Server and skip first n rowsData dashboard for SQL server databaseNot enough replicas available for query at consistency all (2 required but only 1 alive)Natural Language to SQL queryCall a SQL procedure, for each group byPython-SQL database
$begingroup$
We are working on a project that tries to accelerate Spark SQL using dedicated hardware.
Our approach works much better (in terms of the resulting latency) if we allow query processing that is only probably correct.
That is, with high probability (e.g., 99.9%) we will return the correct answer.
I was wondering if such there are any existing systems with such a guarantee. The closest I've seen is the "approximate percentile" computation, but this also has an error in the result (whereas we give the exact result with high probability).
Thanks!
bigdata apache-spark probability sql
New contributor
$endgroup$
add a comment |
$begingroup$
We are working on a project that tries to accelerate Spark SQL using dedicated hardware.
Our approach works much better (in terms of the resulting latency) if we allow query processing that is only probably correct.
That is, with high probability (e.g., 99.9%) we will return the correct answer.
I was wondering if such there are any existing systems with such a guarantee. The closest I've seen is the "approximate percentile" computation, but this also has an error in the result (whereas we give the exact result with high probability).
Thanks!
bigdata apache-spark probability sql
New contributor
$endgroup$
add a comment |
$begingroup$
We are working on a project that tries to accelerate Spark SQL using dedicated hardware.
Our approach works much better (in terms of the resulting latency) if we allow query processing that is only probably correct.
That is, with high probability (e.g., 99.9%) we will return the correct answer.
I was wondering if such there are any existing systems with such a guarantee. The closest I've seen is the "approximate percentile" computation, but this also has an error in the result (whereas we give the exact result with high probability).
Thanks!
bigdata apache-spark probability sql
New contributor
$endgroup$
We are working on a project that tries to accelerate Spark SQL using dedicated hardware.
Our approach works much better (in terms of the resulting latency) if we allow query processing that is only probably correct.
That is, with high probability (e.g., 99.9%) we will return the correct answer.
I was wondering if such there are any existing systems with such a guarantee. The closest I've seen is the "approximate percentile" computation, but this also has an error in the result (whereas we give the exact result with high probability).
Thanks!
bigdata apache-spark probability sql
bigdata apache-spark probability sql
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Jenny is a new contributor. Be nice, and check out our Code of Conduct.
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