Comments (4)
This implemented as part of dask - you could do something similar without dask, using threads or whatever, if you wished.
from fastparquet.
can you please provide some reference how it can be done manually (without dask). I couldn't find the relevant info in the project documentation
from fastparquet.
The easiest would probably be to write each data-frame to a separate parquet file in the same directory, parallelized in whatever manner is suitable to you, and then call merge()
when done. Looking at the code of merge()
, you will see that it loads in some metadata from each file, which you could in theory be avoided with a little extra code.
from fastparquet.
Many thanks!
from fastparquet.
Related Issues (20)
- to_pandas(): cramjam.DecompressionError: snappy: output buffer (size = 262144) is smaller than required (size = 1048576) HOT 1
- BUG: dataframe.empty with non-nano pd.DatetimeTZDtype HOT 2
- a python-3.12 windows wheel HOT 13
- Some `fastparquet`-related tests are failing on Python 3.10 HOT 10
- Regression due to `_from_sequence` HOT 1
- attrs persistance for Pandas HOT 1
- Nullable types for 1 row vs multiple rows HOT 3
- update_file_custom_metadata error when file has no properties.
- schema evolution when writing the row groups does not work HOT 4
- Bug loading parquet files with timezone information HOT 6
- When changing to a larger dtype, its size must be a advisor of the total size in bytes of the last axis of the array HOT 6
- PyArrow will become a required dependency with pandas 3.0
- Option to not close() after write() when writing to buffer HOT 3
- Support zoneinfo.ZoneInfo timezones
- Loading List of List of Strings leads to nans HOT 6
- Upcoming pandas (>2.2.0) raises "read-only" errors HOT 3
- Categorical dtype not preserved with fastparquet-write, pyarrow-read HOT 2
- Numpy 2: OverflowError with int96 HOT 4
- Fastparquet raises on import with numpy 2.0 rc HOT 5
- New release? HOT 4
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from fastparquet.