src/paimon/common/data/shredding/map_shared_shredding_context_test.cpp

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 * to you under the Apache License, Version 2.0 (the
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#include "paimon/common/data/shredding/map_shared_shredding_context.h"

#include <cstdint>
#include <map>
#include <vector>

#include "gtest/gtest.h"

namespace paimon::test {

TEST(MapSharedShreddingContextTest, FirstFileUsesKMax) {
    // No history — ComputeNextK should return K_max for every column.
    std::map<std::string, int32_t> field_to_k_max = {{"tags", 8}, {"metrics", 4}};
    MapSharedShreddingContext context(field_to_k_max);

    auto next_k = context.ComputeNextK();
    ASSERT_EQ(2, next_k.size());
    ASSERT_EQ(8, next_k.at("tags"));
    ASSERT_EQ(4, next_k.at("metrics"));
}

TEST(MapSharedShreddingContextTest, AdaptKAfterOneFile) {
    // After reporting stats from one file, K should adapt to
    // min(adaptive width, K_max).
    std::map<std::string, int32_t> field_to_k_max = {{"m", 10}};
    MapSharedShreddingContext context(field_to_k_max);

    // First file uses K_max=10.
    auto k1 = context.ComputeNextK();
    ASSERT_EQ(10, k1.at("m"));

    // Report: file had max_row_width=3 for field "m".
    context.ReportFileStats("m", 3);

    // Second file: K = min(3, 10) = 3.
    auto k2 = context.ComputeNextK();
    ASSERT_EQ(3, k2.at("m"));
}

TEST(MapSharedShreddingContextTest, AdaptKCappedByKMax) {
    // Even if max_row_width > K_max, K should be capped at K_max.
    std::map<std::string, int32_t> field_to_k_max = {{"m", 5}};
    MapSharedShreddingContext context(field_to_k_max);

    context.ReportFileStats("m", 100);

    auto next_k = context.ComputeNextK();
    ASSERT_EQ(5, next_k.at("m"));
}

TEST(MapSharedShreddingContextTest, WindowP90UsesMaxWhenSamplesAreClose) {
    // Small sample windows still use max because max and P90 are close.
    std::map<std::string, int32_t> field_to_k_max = {{"m", 20}};
    MapSharedShreddingContext context(field_to_k_max);

    context.ReportFileStats("m", 3);
    context.ReportFileStats("m", 7);
    context.ReportFileStats("m", 5);

    auto next_k = context.ComputeNextK();
    ASSERT_EQ(7, next_k.at("m"));
}

TEST(MapSharedShreddingContextTest, WindowP90IgnoresSingleFarOutlier) {
    std::map<std::string, int32_t> field_to_k_max = {{"m", 2000}};
    MapSharedShreddingContext context(field_to_k_max);

    for (int32_t i = 0; i < 19; ++i) {
        context.ReportFileStats("m", 3);
    }
    context.ReportFileStats("m", 1000);

    auto next_k = context.ComputeNextK();
    ASSERT_EQ(3, next_k.at("m"));
}

TEST(MapSharedShreddingContextTest, WindowP90UsesMaxWithinAbsoluteSlack) {
    std::map<std::string, int32_t> field_to_k_max = {{"m", 20}};
    MapSharedShreddingContext context(field_to_k_max);

    for (int32_t i = 0; i < 19; ++i) {
        context.ReportFileStats("m", 3);
    }
    context.ReportFileStats("m", 7);

    auto next_k = context.ComputeNextK();
    ASSERT_EQ(7, next_k.at("m"));
}

TEST(MapSharedShreddingContextTest, WindowP90UsesMaxWithinRelativeSlack) {
    std::map<std::string, int32_t> field_to_k_max = {{"m", 200}};
    MapSharedShreddingContext context(field_to_k_max);

    for (int32_t i = 0; i < 19; ++i) {
        context.ReportFileStats("m", 100);
    }
    context.ReportFileStats("m", 125);

    auto next_k = context.ComputeNextK();
    ASSERT_EQ(125, next_k.at("m"));
}

TEST(MapSharedShreddingContextTest, WindowP90IgnoresMaxBeyondBothSlacks) {
    std::map<std::string, int32_t> field_to_k_max = {{"m", 200}};
    MapSharedShreddingContext context(field_to_k_max);

    for (int32_t i = 0; i < 19; ++i) {
        context.ReportFileStats("m", 100);
    }
    context.ReportFileStats("m", 130);

    auto next_k = context.ComputeNextK();
    ASSERT_EQ(100, next_k.at("m"));
}

TEST(MapSharedShreddingContextTest, MultipleColumnsIndependent) {
    // Each field adapts independently.
    std::map<std::string, int32_t> field_to_k_max = {{"tags", 10}, {"attrs", 6}};
    MapSharedShreddingContext context(field_to_k_max);

    // First file.
    auto k1 = context.ComputeNextK();
    ASSERT_EQ(10, k1.at("tags"));
    ASSERT_EQ(6, k1.at("attrs"));

    // Report: tags had width 4, attrs had width 2.
    context.ReportFileStats("tags", 4);
    context.ReportFileStats("attrs", 2);

    auto k2 = context.ComputeNextK();
    ASSERT_EQ(4, k2.at("tags"));
    ASSERT_EQ(2, k2.at("attrs"));

    // Report: tags had width 8, attrs had width 6.
    context.ReportFileStats("tags", 8);
    context.ReportFileStats("attrs", 6);

    auto k3 = context.ComputeNextK();
    // tags and attrs are close sample windows, so adaptive width keeps max.
    ASSERT_EQ(8, k3.at("tags"));
    ASSERT_EQ(6, k3.at("attrs"));
}

TEST(MapSharedShreddingContextTest, GetShreddingColumnNames) {
    std::map<std::string, int32_t> field_to_k_max = {{"tags", 8}, {"metrics", 4}, {"props", 16}};
    MapSharedShreddingContext context(field_to_k_max);

    auto names = context.GetShreddingColumnNames();
    ASSERT_EQ(names, std::vector<std::string>({"metrics", "props", "tags"}));
}

TEST(MapSharedShreddingContextTest, SlidingWindowEvictsOldEntries) {
    // The window size is 20. After filling 20 entries, adding one more
    // should evict the oldest. Verify that the evicted value no longer
    // affects ComputeNextK.
    std::map<std::string, int32_t> field_to_k_max = {{"m", 256}};
    MapSharedShreddingContext context(field_to_k_max);

    // Insert a large value as the first entry.
    context.ReportFileStats("m", 200);

    // Fill the remaining 19 slots with small values.
    for (int32_t i = 0; i < 19; ++i) {
        context.ReportFileStats("m", 3);
    }

    // Window = [200, 3, 3, ..., 3] (20 entries). P90 = 3, max is a far outlier.
    auto k_before = context.ComputeNextK();
    ASSERT_EQ(3, k_before.at("m"));

    // Push one more — evicts the 200.
    context.ReportFileStats("m", 5);

    // Window = [3, 3, ..., 3, 5] (20 entries). Max is within the absolute slack.
    auto k_after = context.ComputeNextK();
    ASSERT_EQ(5, k_after.at("m"));
}

}  // namespace paimon::test