# Repartitioning 2TB of csv into parquets

**URL:** <https://discourse.julialang.org/t/repartitioning-2tb-of-csv-into-parquets/27716>\
**Category:** Data\
**Tags:** big-data\
**Created:** [August 19, 2019, 2:29pm UTC](https://discourse.julialang.org/t/repartitioning-2tb-of-csv-into-parquets/27716 "2019-08-19T14:29:36Z")\
**Posts on this page:** 1\
**Showing post:** 9

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**Author:** ![johnh](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/johnh/32/3615_2.png) [@johnh](https://discourse.julialang.org/u/johnh)\
**Post date:** [April 17, 2020, 8:56am UTC](https://discourse.julialang.org/t/repartitioning-2tb-of-csv-into-parquets/27716/9 "2020-04-17T08:56:14Z")

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Would DatFramesDBs be of any help?

> [@\[ANN\] DataFrameDBs.jl](https://discourse.julialang.org/t/ann-dataframedbs-jl/35718):
>
> Hi all! Julia is my hobby and I had some free time for the last 4 weeks, so here is the first results of my experiments [GitHub - waralex/DataFrameDBs.jl: The DateFrameDBs is the prototype of persistent, space efficient columnar database on pure Julia](https://github.com/waralex/DataFrameDBs.jl) It is the prototype of columnar, persistent, type stable and space efficient database in pure Julia. Some examples on [this](https://www.kaggle.com/mkechinov/ecommerce-behavior-data-from-multi-category-store) dataset imported to DataFrameDBs julia\> using DataFrameDBs julia\> t = open\_table("ecommerce") DFTable path: ecommerce 10×6…

> **[GitHub - waralex/DataFrameDBs.jl: The DateFrameDBs is the prototype of...](https://github.com/waralex/DataFrameDBs.jl)**
>
> The DateFrameDBs is the prototype of persistent, space efficient columnar database on pure Julia - GitHub - waralex/DataFrameDBs.jl: The DateFrameDBs is the prototype of persistent, space efficient...

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