I’ve done some testing using pyarrow.jvm as part of jdbc optimization.
https://arrow.apache.org/docs/python/integration/python_java.html
Pull a dataset using a JVM environment with JDBC.
Map JDBC arrow result set to a python pyarrow result set.
ra = jpype.JPackage("org").apache.arrow.memory.Roo
Awesome, I will continue on that JIRA.
Thanks!
On Mon, Oct 24, 2022 at 6:23 AM Neal Richardson
wrote:
> Hi Chang,
> I don't recall seeing an Arrow issue about this specifically, or any
> examples of doing that, but that sounds nice.
> https://issues.apache.org/jira/browse/ARROW-17608 (C interfa
To check for null you can use the `is_null` function:
```
import pyarrow as pa
import pyarrow.compute as pc
import pyarrow.dataset as ds
tab = pa.Table.from_pydict({"x": [1, 2, 3, None], "y": ["a", "b", "c",
"d"]})
filtered = ds.dataset(tab).to_table(filter=pc.is_null(pc.field("x")))
print(filter
my Filter Expression:
expression->ToString() get this result??(predict_model != null[string])
That's how I got this expression??
auto null_expr = arrow::compute::Expression(MakeNullScalar(arrow::utf8()));
call(not_equal(field_ref("predict_model"), null_expr))
I then use this expression to filt
Hi Chang,
I don't recall seeing an Arrow issue about this specifically, or any
examples of doing that, but that sounds nice.
https://issues.apache.org/jira/browse/ARROW-17608 (C interface support in
JS) is probably a prerequisite.
Neal
On Sun, Oct 23, 2022 at 2:45 PM Chang She wrote:
> couldn’t
