# How to read a parquet file applying a filter?
**URL:** https://discourse.julialang.org/t/how-to-read-a-parquet-file-applying-a-filter/113982
**Category:** General Usage
**Created:** [May 8, 2024, 5:39am UTC](https://discourse.julialang.org/t/how-to-read-a-parquet-file-applying-a-filter/113982 "2024-05-08T05:39:19Z")
**Posts on this page:** 5
**Page:** 1
### Author:  [@laygr](https://discourse.julialang.org/u/laygr)
#### Post date: [May 8, 2024, 5:39am UTC](https://discourse.julialang.org/t/how-to-read-a-parquet-file-applying-a-filter/113982/1 "2024-05-08T05:39:19Z")
In python, we can do:
```
import pyarrow.parquet as pq
filter = ('some_column', '=', 'some_value')
pq.read_table(file_path, filters=[filter]).to_pandas()
```
How can I apply a filter similarly when reading a parquet file in Julia?
I’ve tried:
```
using Parquet
filter = row -> row.some_column == "some_value"
Parquet.read_parquet(filepath, filter=filter)
```
But I get an error saying that there is no such method:
> Closest candidates are:
> Parquet.Table(::Any, ::Parquet.File, ::Tables.Schema; rows, batchsize, column\_generator, use\_threads) got unsupported keyword argument “filter”
But, according to the source of the [Parquet](https://github.com/JuliaIO/Parquet.jl) package, the `filter` option should be supported… it says:
> `filter`: Filter function to apply while loading only a subset of partitions from a dataset. The path to the partition is provided as a parameter.
The only thing that I’ve got working is:
```
using Parquet2
return Parquet2.Dataset(file_path) |> TableOperations.filter(r -> Tables.getcolumn(r, :some_column) == some_value) |> DataFrames.DataFrame
```
But this is much slower than the Python solution.
---
### Author:  [@rdavis120](https://discourse.julialang.org/u/rdavis120)
#### Post date: [May 8, 2024, 7:56am UTC](https://discourse.julialang.org/t/how-to-read-a-parquet-file-applying-a-filter/113982/2 "2024-05-08T07:56:39Z")
Maybe try something like this:
```julia
using DuckDB, DataFrames
db = DuckDB.DB()
DuckDB.query(db, "select * from '/path/*.parquet' where some_column = some_value") |> DataFrames.DataFrame
```
---
### Author:  [@laygr](https://discourse.julialang.org/u/laygr)
#### Post date: [May 8, 2024, 6:08pm UTC](https://discourse.julialang.org/t/how-to-read-a-parquet-file-applying-a-filter/113982/4 "2024-05-08T18:08:18Z")
Yeah, there is a slight but noticeable speedup. Thanks!
🦆 to the rescue.
Do you know how I could read in chunks using DuckDB?
Some parquet files don’t fit in my RAM even after applying the WHERE clause.
---
### Author:  [@rdavis120](https://discourse.julialang.org/u/rdavis120)
#### Post date: [May 8, 2024, 6:51pm UTC](https://discourse.julialang.org/t/how-to-read-a-parquet-file-applying-a-filter/113982/5 "2024-05-08T18:51:06Z")
Yes it is supported by the duckdb library and the Julia client api. You can see an example [here](https://github.com/duckdb/duckdb/blob/d9efdd14270245c4369096e909acecea174d86cc/tools/juliapkg/test/test_stream_data_chunk.jl#L41) in tests.
The issue is that the Tables _partitions_ interface is not yet supported in the client api. If someone knew the tables partition interface well enough to contribute, it would help.
---
### Author:  [@laygr](https://discourse.julialang.org/u/laygr)
#### Post date: [May 9, 2024, 7:12pm UTC](https://discourse.julialang.org/t/how-to-read-a-parquet-file-applying-a-filter/113982/6 "2024-05-09T19:12:59Z")
I appreciate the example, but I’m not getting the expected behavior.
I ran the test and it blew my RAM because instead of streaming the result in chunks, it tried to return the 1000000000000 rows in a single chunk.