| <!DOCTYPE html><html lang="en"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1.0"><meta name="generator" content="rustdoc"><meta name="description" content="Source of the Rust file `/root/.cargo/git/checkouts/tantivy-65d0bbbddbbd5d02/433372d/fastfield_codecs/src/serialize.rs`."><meta name="keywords" content="rust, rustlang, rust-lang"><title>serialize.rs - source</title><link rel="preload" as="font" type="font/woff2" crossorigin href="../../SourceSerif4-Regular.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../FiraSans-Regular.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../FiraSans-Medium.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../SourceCodePro-Regular.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../SourceSerif4-Bold.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../SourceCodePro-Semibold.ttf.woff2"><link rel="stylesheet" href="../../normalize.css"><link rel="stylesheet" href="../../rustdoc.css" id="mainThemeStyle"><link rel="stylesheet" href="../../ayu.css" disabled><link rel="stylesheet" href="../../dark.css" disabled><link rel="stylesheet" href="../../light.css" id="themeStyle"><script id="default-settings" ></script><script src="../../storage.js"></script><script defer src="../../source-script.js"></script><script defer src="../../source-files.js"></script><script defer src="../../main.js"></script><noscript><link rel="stylesheet" href="../../noscript.css"></noscript><link rel="alternate icon" type="image/png" href="../../favicon-16x16.png"><link rel="alternate icon" type="image/png" href="../../favicon-32x32.png"><link rel="icon" type="image/svg+xml" href="../../favicon.svg"></head><body class="rustdoc source"><!--[if lte IE 11]><div class="warning">This old browser is unsupported and will most likely display funky things.</div><![endif]--><nav class="sidebar"><a class="sidebar-logo" href="../../fastfield_codecs/index.html"><div class="logo-container"><img class="rust-logo" src="../../rust-logo.svg" alt="logo"></div></a></nav><main><div class="width-limiter"><nav class="sub"><a class="sub-logo-container" href="../../fastfield_codecs/index.html"><img class="rust-logo" src="../../rust-logo.svg" alt="logo"></a><form class="search-form"><div class="search-container"><span></span><input class="search-input" name="search" autocomplete="off" spellcheck="false" placeholder="Click or press ‘S’ to search, ‘?’ for more options…" type="search"><div id="help-button" title="help" tabindex="-1"><a href="../../help.html">?</a></div><div id="settings-menu" tabindex="-1"><a href="../../settings.html" title="settings"><img width="22" height="22" alt="Change settings" src="../../wheel.svg"></a></div></div></form></nav><section id="main-content" class="content"><div class="example-wrap"><pre class="src-line-numbers"><span id="1">1</span> |
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| </pre><pre class="rust"><code><span class="comment">// Copyright (C) 2022 Quickwit, Inc. |
| // |
| // Quickwit is offered under the AGPL v3.0 and as commercial software. |
| // For commercial licensing, contact us at hello@quickwit.io. |
| // |
| // AGPL: |
| // This program is free software: you can redistribute it and/or modify |
| // it under the terms of the GNU Affero General Public License as |
| // published by the Free Software Foundation, either version 3 of the |
| // License, or (at your option) any later version. |
| // |
| // This program is distributed in the hope that it will be useful, |
| // but WITHOUT ANY WARRANTY; without even the implied warranty of |
| // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| // GNU Affero General Public License for more details. |
| // |
| // You should have received a copy of the GNU Affero General Public License |
| // along with this program. If not, see <http://www.gnu.org/licenses/>. |
| |
| </span><span class="kw">use </span>std::num::NonZeroU64; |
| <span class="kw">use </span>std::sync::Arc; |
| <span class="kw">use </span>std::{fmt, io}; |
| |
| <span class="kw">use </span>common::{BinarySerializable, VInt}; |
| <span class="kw">use </span>log::warn; |
| <span class="kw">use </span>ownedbytes::OwnedBytes; |
| |
| <span class="kw">use </span><span class="kw">crate</span>::bitpacked::BitpackedCodec; |
| <span class="kw">use </span><span class="kw">crate</span>::blockwise_linear::BlockwiseLinearCodec; |
| <span class="kw">use </span><span class="kw">crate</span>::compact_space::CompactSpaceCompressor; |
| <span class="kw">use </span><span class="kw">crate</span>::format_version::append_format_version; |
| <span class="kw">use </span><span class="kw">crate</span>::linear::LinearCodec; |
| <span class="kw">use </span><span class="kw">crate</span>::monotonic_mapping::{ |
| StrictlyMonotonicFn, StrictlyMonotonicMappingToInternal, |
| StrictlyMonotonicMappingToInternalGCDBaseval, |
| }; |
| <span class="kw">use </span><span class="kw">crate</span>::null_index_footer::{ |
| append_null_index_footer, FastFieldCardinality, NullIndexCodec, NullIndexFooter, |
| }; |
| <span class="kw">use crate</span>::{ |
| monotonic_map_column, Column, FastFieldCodec, FastFieldCodecType, MonotonicallyMappableToU64, |
| U128FastFieldCodecType, VecColumn, ALL_CODEC_TYPES, |
| }; |
| |
| <span class="doccomment">/// The normalized header gives some parameters after applying the following |
| /// normalization of the vector: |
| /// `val -> (val - min_value) / gcd` |
| /// |
| /// By design, after normalization, `min_value = 0` and `gcd = 1`. |
| </span><span class="attribute">#[derive(Debug, Copy, Clone)] |
| </span><span class="kw">pub struct </span>NormalizedHeader { |
| <span class="doccomment">/// The number of values in the underlying column. |
| </span><span class="kw">pub </span>num_vals: u32, |
| <span class="doccomment">/// The max value of the underlying column. |
| </span><span class="kw">pub </span>max_value: u64, |
| } |
| |
| <span class="attribute">#[derive(Debug, Copy, Clone)] |
| </span><span class="kw">pub</span>(<span class="kw">crate</span>) <span class="kw">struct </span>Header { |
| <span class="kw">pub </span>num_vals: u32, |
| <span class="kw">pub </span>min_value: u64, |
| <span class="kw">pub </span>max_value: u64, |
| <span class="kw">pub </span>gcd: <span class="prelude-ty">Option</span><NonZeroU64>, |
| <span class="kw">pub </span>codec_type: FastFieldCodecType, |
| } |
| |
| <span class="kw">impl </span>Header { |
| <span class="kw">pub fn </span>normalized(<span class="self">self</span>) -> NormalizedHeader { |
| <span class="kw">let </span>gcd = <span class="self">self</span>.gcd.map(|gcd| gcd.get()).unwrap_or(<span class="number">1</span>); |
| <span class="kw">let </span>gcd_min_val_mapping = |
| StrictlyMonotonicMappingToInternalGCDBaseval::new(gcd, <span class="self">self</span>.min_value); |
| |
| <span class="kw">let </span>max_value = gcd_min_val_mapping.mapping(<span class="self">self</span>.max_value); |
| NormalizedHeader { |
| num_vals: <span class="self">self</span>.num_vals, |
| max_value, |
| } |
| } |
| |
| <span class="kw">pub fn </span>normalize_column<C: Column>(<span class="kw-2">&</span><span class="self">self</span>, from_column: C) -> <span class="kw">impl </span>Column { |
| normalize_column(from_column, <span class="self">self</span>.min_value, <span class="self">self</span>.gcd) |
| } |
| |
| <span class="kw">pub fn </span>compute_header( |
| column: <span class="kw">impl </span>Column<u64>, |
| codecs: <span class="kw-2">&</span>[FastFieldCodecType], |
| ) -> <span class="prelude-ty">Option</span><Header> { |
| <span class="kw">let </span>num_vals = column.num_vals(); |
| <span class="kw">let </span>min_value = column.min_value(); |
| <span class="kw">let </span>max_value = column.max_value(); |
| <span class="kw">let </span>gcd = <span class="kw">crate</span>::gcd::find_gcd(column.iter().map(|val| val - min_value)) |
| .filter(|gcd| gcd.get() > <span class="number">1u64</span>); |
| <span class="kw">let </span>normalized_column = normalize_column(column, min_value, gcd); |
| <span class="kw">let </span>codec_type = detect_codec(normalized_column, codecs)<span class="question-mark">?</span>; |
| <span class="prelude-val">Some</span>(Header { |
| num_vals, |
| min_value, |
| max_value, |
| gcd, |
| codec_type, |
| }) |
| } |
| } |
| |
| <span class="attribute">#[derive(Debug, Copy, Clone, PartialEq, Eq)] |
| </span><span class="kw">pub</span>(<span class="kw">crate</span>) <span class="kw">struct </span>U128Header { |
| <span class="kw">pub </span>num_vals: u32, |
| <span class="kw">pub </span>codec_type: U128FastFieldCodecType, |
| } |
| |
| <span class="kw">impl </span>BinarySerializable <span class="kw">for </span>U128Header { |
| <span class="kw">fn </span>serialize<W: io::Write>(<span class="kw-2">&</span><span class="self">self</span>, writer: <span class="kw-2">&mut </span>W) -> io::Result<()> { |
| VInt(<span class="self">self</span>.num_vals <span class="kw">as </span>u64).serialize(writer)<span class="question-mark">?</span>; |
| <span class="self">self</span>.codec_type.serialize(writer)<span class="question-mark">?</span>; |
| <span class="prelude-val">Ok</span>(()) |
| } |
| |
| <span class="kw">fn </span>deserialize<R: io::Read>(reader: <span class="kw-2">&mut </span>R) -> io::Result<<span class="self">Self</span>> { |
| <span class="kw">let </span>num_vals = VInt::deserialize(reader)<span class="question-mark">?</span>.<span class="number">0 </span><span class="kw">as </span>u32; |
| <span class="kw">let </span>codec_type = U128FastFieldCodecType::deserialize(reader)<span class="question-mark">?</span>; |
| <span class="prelude-val">Ok</span>(U128Header { |
| num_vals, |
| codec_type, |
| }) |
| } |
| } |
| |
| <span class="kw">pub fn </span>normalize_column<C: Column>( |
| from_column: C, |
| min_value: u64, |
| gcd: <span class="prelude-ty">Option</span><NonZeroU64>, |
| ) -> <span class="kw">impl </span>Column { |
| <span class="kw">let </span>gcd = gcd.map(|gcd| gcd.get()).unwrap_or(<span class="number">1</span>); |
| <span class="kw">let </span>mapping = StrictlyMonotonicMappingToInternalGCDBaseval::new(gcd, min_value); |
| monotonic_map_column(from_column, mapping) |
| } |
| |
| <span class="kw">impl </span>BinarySerializable <span class="kw">for </span>Header { |
| <span class="kw">fn </span>serialize<W: io::Write>(<span class="kw-2">&</span><span class="self">self</span>, writer: <span class="kw-2">&mut </span>W) -> io::Result<()> { |
| VInt(<span class="self">self</span>.num_vals <span class="kw">as </span>u64).serialize(writer)<span class="question-mark">?</span>; |
| VInt(<span class="self">self</span>.min_value).serialize(writer)<span class="question-mark">?</span>; |
| VInt(<span class="self">self</span>.max_value - <span class="self">self</span>.min_value).serialize(writer)<span class="question-mark">?</span>; |
| <span class="kw">if let </span><span class="prelude-val">Some</span>(gcd) = <span class="self">self</span>.gcd { |
| VInt(gcd.get()).serialize(writer)<span class="question-mark">?</span>; |
| } <span class="kw">else </span>{ |
| VInt(<span class="number">0u64</span>).serialize(writer)<span class="question-mark">?</span>; |
| } |
| <span class="self">self</span>.codec_type.serialize(writer)<span class="question-mark">?</span>; |
| <span class="prelude-val">Ok</span>(()) |
| } |
| |
| <span class="kw">fn </span>deserialize<R: io::Read>(reader: <span class="kw-2">&mut </span>R) -> io::Result<<span class="self">Self</span>> { |
| <span class="kw">let </span>num_vals = VInt::deserialize(reader)<span class="question-mark">?</span>.<span class="number">0 </span><span class="kw">as </span>u32; |
| <span class="kw">let </span>min_value = VInt::deserialize(reader)<span class="question-mark">?</span>.<span class="number">0</span>; |
| <span class="kw">let </span>amplitude = VInt::deserialize(reader)<span class="question-mark">?</span>.<span class="number">0</span>; |
| <span class="kw">let </span>max_value = min_value + amplitude; |
| <span class="kw">let </span>gcd_u64 = VInt::deserialize(reader)<span class="question-mark">?</span>.<span class="number">0</span>; |
| <span class="kw">let </span>codec_type = FastFieldCodecType::deserialize(reader)<span class="question-mark">?</span>; |
| <span class="prelude-val">Ok</span>(Header { |
| num_vals, |
| min_value, |
| max_value, |
| gcd: NonZeroU64::new(gcd_u64), |
| codec_type, |
| }) |
| } |
| } |
| |
| <span class="doccomment">/// Return estimated compression for given codec in the value range [0.0..1.0], where 1.0 means no |
| /// compression. |
| </span><span class="kw">pub fn </span>estimate<T: MonotonicallyMappableToU64 + fmt::Debug>( |
| typed_column: <span class="kw">impl </span>Column<T>, |
| codec_type: FastFieldCodecType, |
| ) -> <span class="prelude-ty">Option</span><f32> { |
| <span class="kw">let </span>column = monotonic_map_column(typed_column, StrictlyMonotonicMappingToInternal::<T>::new()); |
| <span class="kw">let </span>min_value = column.min_value(); |
| <span class="kw">let </span>gcd = <span class="kw">crate</span>::gcd::find_gcd(column.iter().map(|val| val - min_value)) |
| .filter(|gcd| gcd.get() > <span class="number">1u64</span>); |
| <span class="kw">let </span>mapping = StrictlyMonotonicMappingToInternalGCDBaseval::new( |
| gcd.map(|gcd| gcd.get()).unwrap_or(<span class="number">1u64</span>), |
| min_value, |
| ); |
| <span class="kw">let </span>normalized_column = monotonic_map_column(<span class="kw-2">&</span>column, mapping); |
| <span class="kw">match </span>codec_type { |
| FastFieldCodecType::Bitpacked => BitpackedCodec::estimate(<span class="kw-2">&</span>normalized_column), |
| FastFieldCodecType::Linear => LinearCodec::estimate(<span class="kw-2">&</span>normalized_column), |
| FastFieldCodecType::BlockwiseLinear => BlockwiseLinearCodec::estimate(<span class="kw-2">&</span>normalized_column), |
| } |
| } |
| |
| <span class="doccomment">/// Serializes u128 values with the compact space codec. |
| </span><span class="kw">pub fn </span>serialize_u128<F: Fn() -> I, I: Iterator<Item = u128>>( |
| iter_gen: F, |
| num_vals: u32, |
| output: <span class="kw-2">&mut </span><span class="kw">impl </span>io::Write, |
| ) -> io::Result<()> { |
| <span class="kw">let </span>header = U128Header { |
| num_vals, |
| codec_type: U128FastFieldCodecType::CompactSpace, |
| }; |
| header.serialize(output)<span class="question-mark">?</span>; |
| <span class="kw">let </span>compressor = CompactSpaceCompressor::train_from(iter_gen(), num_vals); |
| compressor.compress_into(iter_gen(), output).unwrap(); |
| |
| <span class="kw">let </span>null_index_footer = NullIndexFooter { |
| cardinality: FastFieldCardinality::Single, |
| null_index_codec: NullIndexCodec::Full, |
| null_index_byte_range: <span class="number">0</span>..<span class="number">0</span>, |
| }; |
| append_null_index_footer(output, null_index_footer)<span class="question-mark">?</span>; |
| append_format_version(output)<span class="question-mark">?</span>; |
| |
| <span class="prelude-val">Ok</span>(()) |
| } |
| |
| <span class="doccomment">/// Serializes the column with the codec with the best estimate on the data. |
| </span><span class="kw">pub fn </span>serialize<T: MonotonicallyMappableToU64 + fmt::Debug>( |
| typed_column: <span class="kw">impl </span>Column<T>, |
| output: <span class="kw-2">&mut </span><span class="kw">impl </span>io::Write, |
| codecs: <span class="kw-2">&</span>[FastFieldCodecType], |
| ) -> io::Result<()> { |
| <span class="kw">let </span>column = monotonic_map_column(typed_column, StrictlyMonotonicMappingToInternal::<T>::new()); |
| <span class="kw">let </span>header = Header::compute_header(<span class="kw-2">&</span>column, codecs).ok_or_else(|| { |
| io::Error::new( |
| io::ErrorKind::InvalidInput, |
| <span class="macro">format!</span>( |
| <span class="string">"Data cannot be serialized with this list of codec. {:?}"</span>, |
| codecs |
| ), |
| ) |
| })<span class="question-mark">?</span>; |
| header.serialize(output)<span class="question-mark">?</span>; |
| <span class="kw">let </span>normalized_column = header.normalize_column(column); |
| <span class="macro">assert_eq!</span>(normalized_column.min_value(), <span class="number">0u64</span>); |
| serialize_given_codec(normalized_column, header.codec_type, output)<span class="question-mark">?</span>; |
| |
| <span class="kw">let </span>null_index_footer = NullIndexFooter { |
| cardinality: FastFieldCardinality::Single, |
| null_index_codec: NullIndexCodec::Full, |
| null_index_byte_range: <span class="number">0</span>..<span class="number">0</span>, |
| }; |
| append_null_index_footer(output, null_index_footer)<span class="question-mark">?</span>; |
| append_format_version(output)<span class="question-mark">?</span>; |
| |
| <span class="prelude-val">Ok</span>(()) |
| } |
| |
| <span class="kw">fn </span>detect_codec( |
| column: <span class="kw">impl </span>Column<u64>, |
| codecs: <span class="kw-2">&</span>[FastFieldCodecType], |
| ) -> <span class="prelude-ty">Option</span><FastFieldCodecType> { |
| <span class="kw">let </span><span class="kw-2">mut </span>estimations = Vec::new(); |
| <span class="kw">for </span><span class="kw-2">&</span>codec <span class="kw">in </span>codecs { |
| <span class="kw">let </span>estimation_opt = <span class="kw">match </span>codec { |
| FastFieldCodecType::Bitpacked => BitpackedCodec::estimate(<span class="kw-2">&</span>column), |
| FastFieldCodecType::Linear => LinearCodec::estimate(<span class="kw-2">&</span>column), |
| FastFieldCodecType::BlockwiseLinear => BlockwiseLinearCodec::estimate(<span class="kw-2">&</span>column), |
| }; |
| <span class="kw">if let </span><span class="prelude-val">Some</span>(estimation) = estimation_opt { |
| estimations.push((estimation, codec)); |
| } |
| } |
| <span class="kw">if let </span><span class="prelude-val">Some</span>(broken_estimation) = estimations.iter().find(|estimation| estimation.<span class="number">0</span>.is_nan()) { |
| <span class="macro">warn!</span>( |
| <span class="string">"broken estimation for fast field codec {:?}"</span>, |
| broken_estimation.<span class="number">1 |
| </span>); |
| } |
| <span class="comment">// removing nan values for codecs with broken calculations, and max values which disables |
| // codecs |
| </span>estimations.retain(|estimation| !estimation.<span class="number">0</span>.is_nan() && estimation.<span class="number">0 </span>!= f32::MAX); |
| estimations.sort_by(|(score_left, <span class="kw">_</span>), (score_right, <span class="kw">_</span>)| score_left.total_cmp(score_right)); |
| <span class="prelude-val">Some</span>(estimations.first()<span class="question-mark">?</span>.<span class="number">1</span>) |
| } |
| |
| <span class="kw">fn </span>serialize_given_codec( |
| column: <span class="kw">impl </span>Column<u64>, |
| codec_type: FastFieldCodecType, |
| output: <span class="kw-2">&mut </span><span class="kw">impl </span>io::Write, |
| ) -> io::Result<()> { |
| <span class="kw">match </span>codec_type { |
| FastFieldCodecType::Bitpacked => { |
| BitpackedCodec::serialize(<span class="kw-2">&</span>column, output)<span class="question-mark">?</span>; |
| } |
| FastFieldCodecType::Linear => { |
| LinearCodec::serialize(<span class="kw-2">&</span>column, output)<span class="question-mark">?</span>; |
| } |
| FastFieldCodecType::BlockwiseLinear => { |
| BlockwiseLinearCodec::serialize(<span class="kw-2">&</span>column, output)<span class="question-mark">?</span>; |
| } |
| } |
| output.flush()<span class="question-mark">?</span>; |
| <span class="prelude-val">Ok</span>(()) |
| } |
| |
| <span class="doccomment">/// Helper function to serialize a column (autodetect from all codecs) and then open it |
| </span><span class="kw">pub fn </span>serialize_and_load<T: MonotonicallyMappableToU64 + Ord + Default + fmt::Debug>( |
| column: <span class="kw-2">&</span>[T], |
| ) -> Arc<<span class="kw">dyn </span>Column<T>> { |
| <span class="kw">let </span><span class="kw-2">mut </span>buffer = Vec::new(); |
| <span class="kw">super</span>::serialize(VecColumn::from(<span class="kw-2">&</span>column), <span class="kw-2">&mut </span>buffer, <span class="kw-2">&</span>ALL_CODEC_TYPES).unwrap(); |
| <span class="kw">super</span>::open(OwnedBytes::new(buffer)).unwrap() |
| } |
| |
| <span class="attribute">#[cfg(test)] |
| </span><span class="kw">mod </span>tests { |
| <span class="kw">use super</span>::<span class="kw-2">*</span>; |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>test_serialize_deserialize_u128_header() { |
| <span class="kw">let </span>original = U128Header { |
| num_vals: <span class="number">11</span>, |
| codec_type: U128FastFieldCodecType::CompactSpace, |
| }; |
| <span class="kw">let </span><span class="kw-2">mut </span>out = Vec::new(); |
| original.serialize(<span class="kw-2">&mut </span>out).unwrap(); |
| <span class="kw">let </span>restored = U128Header::deserialize(<span class="kw-2">&mut &</span>out[..]).unwrap(); |
| <span class="macro">assert_eq!</span>(restored, original); |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>test_serialize_deserialize() { |
| <span class="kw">let </span>original = [<span class="number">1u64</span>, <span class="number">5u64</span>, <span class="number">10u64</span>]; |
| <span class="kw">let </span>restored: Vec<u64> = serialize_and_load(<span class="kw-2">&</span>original[..]).iter().collect(); |
| <span class="macro">assert_eq!</span>(<span class="kw-2">&</span>restored, <span class="kw-2">&</span>original[..]); |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>test_fastfield_bool_size_bitwidth_1() { |
| <span class="kw">let </span><span class="kw-2">mut </span>buffer = Vec::new(); |
| <span class="kw">let </span>col = VecColumn::from(<span class="kw-2">&</span>[<span class="bool-val">false</span>, <span class="bool-val">true</span>][..]); |
| serialize(col, <span class="kw-2">&mut </span>buffer, <span class="kw-2">&</span>ALL_CODEC_TYPES).unwrap(); |
| <span class="comment">// 5 bytes of header, 1 byte of value, 7 bytes of padding. |
| </span><span class="macro">assert_eq!</span>(buffer.len(), <span class="number">3 </span>+ <span class="number">5 </span>+ <span class="number">8 </span>+ <span class="number">4 </span>+ <span class="number">2</span>); |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>test_fastfield_bool_bit_size_bitwidth_0() { |
| <span class="kw">let </span><span class="kw-2">mut </span>buffer = Vec::new(); |
| <span class="kw">let </span>col = VecColumn::from(<span class="kw-2">&</span>[<span class="bool-val">true</span>][..]); |
| serialize(col, <span class="kw-2">&mut </span>buffer, <span class="kw-2">&</span>ALL_CODEC_TYPES).unwrap(); |
| <span class="comment">// 5 bytes of header, 0 bytes of value, 7 bytes of padding. |
| </span><span class="macro">assert_eq!</span>(buffer.len(), <span class="number">3 </span>+ <span class="number">5 </span>+ <span class="number">7 </span>+ <span class="number">4 </span>+ <span class="number">2</span>); |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>test_fastfield_gcd() { |
| <span class="kw">let </span><span class="kw-2">mut </span>buffer = Vec::new(); |
| <span class="kw">let </span>vals: Vec<u64> = (<span class="number">0</span>..<span class="number">80</span>).map(|val| (val % <span class="number">7</span>) * <span class="number">1_000u64</span>).collect(); |
| <span class="kw">let </span>col = VecColumn::from(<span class="kw-2">&</span>vals[..]); |
| serialize(col, <span class="kw-2">&mut </span>buffer, <span class="kw-2">&</span>[FastFieldCodecType::Bitpacked]).unwrap(); |
| <span class="comment">// Values are stored over 3 bits. |
| </span><span class="macro">assert_eq!</span>(buffer.len(), <span class="number">3 </span>+ <span class="number">7 </span>+ (<span class="number">3 </span>* <span class="number">80 </span>/ <span class="number">8</span>) + <span class="number">7 </span>+ <span class="number">4 </span>+ <span class="number">2</span>); |
| } |
| } |
| </code></pre></div> |
| </section></div></main><div id="rustdoc-vars" data-root-path="../../" data-current-crate="fastfield_codecs" data-themes="ayu,dark,light" data-resource-suffix="" data-rustdoc-version="1.66.0-nightly (5c8bff74b 2022-10-21)" ></div></body></html> |
