Sail – Unify stream processing, batch processing and compute-intensive workloads
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Re: Sail – Unify stream processing, batch processing and compute-intensive workloads
#2Kinda early to call this a drop in replacement with those numbers no?
But, with enough parity this project could be a dream for anybody dealing with spark’s dreadful performance. Kudos to the team
Re: Sail – Unify stream processing, batch processing and compute-intensive workloads
#3From the announcement “As of now, we have mined 1,580 PySpark tests from the Spark codebase, among which 838 (53.0%) are successful on Sail. We have also mined 2,230 Spark SQL statements or expressions, among which 1,396 (62.6%) can be parsed by Sail” Kinda early to call this a drop in replacement with those numbers no? But, with enough parity this project could be a dream for anybody dealing with spark’s dreadful pe…
I am with you that it is still very very early. I'll personally keep an eye on the project.
Re: Sail – Unify stream processing, batch processing and compute-intensive workloads
#4Re: Sail – Unify stream processing, batch processing and compute-intensive workloads
#5The documentation has nothing to indicate that it is.
Re: Sail – Unify stream processing, batch processing and compute-intensive workloads
#6Re: Sail – Unify stream processing, batch processing and compute-intensive workloads
#7Re: Sail – Unify stream processing, batch processing and compute-intensive workloads
#8From the announcement “As of now, we have mined 1,580 PySpark tests from the Spark codebase, among which 838 (53.0%) are successful on Sail. We have also mined 2,230 Spark SQL statements or expressions, among which 1,396 (62.6%) can be parsed by Sail” Kinda early to call this a drop in replacement with those numbers no? But, with enough parity this project could be a dream for anybody dealing with spark’s dreadful pe…
The next paragraph explains that: "When looking at the test coverage numbers alone, Sail’s capability may seem limited. But we have found that there is a long tail of failed tests due to formatting discrepancies, edge cases, and less-used SQL functions, which we will continue tackling in future releases." I am with you that it is still very very early. I'll personally keep an eye on the project.
Re: Sail – Unify stream processing, batch processing and compute-intensive workloads
#9From the announcement “As of now, we have mined 1,580 PySpark tests from the Spark codebase, among which 838 (53.0%) are successful on Sail. We have also mined 2,230 Spark SQL statements or expressions, among which 1,396 (62.6%) can be parsed by Sail” Kinda early to call this a drop in replacement with those numbers no? But, with enough parity this project could be a dream for anybody dealing with spark’s dreadful pe…
The next paragraph explains that: "When looking at the test coverage numbers alone, Sail’s capability may seem limited. But we have found that there is a long tail of failed tests due to formatting discrepancies, edge cases, and less-used SQL functions, which we will continue tackling in future releases." I am with you that it is still very very early. I'll personally keep an eye on the project.
Re: Sail – Unify stream processing, batch processing and compute-intensive workloads
#10Earlier quoted context omitted.
The next paragraph explains that: "When looking at the test coverage numbers alone, Sail’s capability may seem limited. But we have found that there is a long tail of failed tests due to formatting discrepancies, edge cases, and less-used SQL functions, which we will continue tackling in future releases." I am with you that it is still very very early. I'll personally keep an eye on the project.
I'll keep an eye on it too, but for a query engine formatting compliance and edge cases tend to be almost all of the work. It's easy to implement SELECT x FROM y WHERE z.