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articles/aw_interpolation.html

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articles/benchmark.html

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articles/benchmark.md

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@@ -111,8 +111,8 @@ memo_diff <- round(as.numeric(temp$mem_alloc[2] / temp$mem_alloc[1]),1)
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time_diff <- (1 - round(as.numeric(temp$median[1] / temp$median[2]),2))*100
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```
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In this example working with 1 million points, {duckspatial} was 59%
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faster and used 5.4 times less memory than {sf}. Not bad.
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In this example working with 1 million points, {duckspatial} was 62%
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faster and used 5.5 times less memory than {sf}. Not bad.
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``` r
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ggplot(data = df_bench_join) +
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time_diff <- (1 - round(as.numeric(temp$median[1] / temp$median[2]),2))*100
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```
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In this example working with 1 million points, {duckspatial} was 65%
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In this example working with 1 million points, {duckspatial} was 75%
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faster and used 2.6 times less memory than {sf}.
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plot
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dplyr::bind_rows()
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#> Warning: Some expressions had a GC in every iteration; so filtering is
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#> disabled.
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#> Warning: Some expressions had a GC in every iteration; so filtering is
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#> disabled.
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#> Warning: Some expressions had a GC in every iteration; so filtering is
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#> disabled.
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# calculate difference in performance
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articles/duckspatial.html

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articles/spatial_joins.html

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pkgdown.yml

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@@ -6,7 +6,7 @@ articles:
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benchmark: benchmark.html
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duckspatial: duckspatial.html
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spatial_joins: spatial_joins.html
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last_built: 2026-01-17T15:16Z
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last_built: 2026-01-25T18:24Z
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urls:
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reference: https://cidree.github.io/duckspatial/reference
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article: https://cidree.github.io/duckspatial/articles

search.json

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