Single and partitioned variants for datafusion-vortex

datafusion-vortex-partitioned/README.md

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+# DataFusion + Vortex
+
+Partitioned Vortex dataset, converted one-for-one from the 100 ClickBench Parquet files and queried with [`vortex-datafusion-cli`].
+
+[`vortex-datafusion-cli`]: https://github.com/vortex-data/vortex-datafusion-cli
+
+## Cookbook: Generate benchmark results
+
+Follow the same EC2 setup used by [datafusion-partitioned](../datafusion-partitioned/README.md), then run:
+
+```bash
+cd ClickBench/datafusion-vortex-partitioned
+bash benchmark.sh
+```
+
+The benchmark script builds `vortex-datafusion-cli`, downloads the partitioned Parquet files, converts each `partitioned/hits_N.parquet` file into exactly one `vortex/hits_N.vortex` file, and runs the query set.
+
+`benchmark.sh` checks out `vortex-datafusion-cli` tag `0.70.0-53.1.0`. CLI tags use `<vortex-version>-<df-version>`, where the first component is the `vortex-datafusion` crate version and the second is the DataFusion/DataFusion CLI version.
+
+You can update/preview the results by running:
+
+```bash
+./make-json.sh <machine-name> # Example. ./make-json.sh c6a.xlarge
+```
+
+## Parquet to Vortex conversion
+
+Each input file is converted independently through `vortex-datafusion-cli`:
+
+```sql
+CREATE EXTERNAL TABLE hits_parquet
+STORED AS PARQUET
+LOCATION 'partitioned/hits_0.parquet'
+OPTIONS ('binary_as_string' 'true');
+
+COPY (
+    SELECT * EXCEPT ("EventDate"),
+           CAST(CAST("EventDate" AS INTEGER) AS DATE) AS "EventDate"
+    FROM hits_parquet
+) TO 'vortex/hits_0.vortex' STORED AS VORTEX;
+```
+
+`binary_as_string=true` handles the incorrect Parquet logical annotation before Vortex is written. The produced Vortex files store those fields as strings, so benchmark reads use only the Vortex table registration.

datafusion-vortex-partitioned/benchmark.sh

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+#!/bin/bash
+
+set -Eeuo pipefail
+
+export HOME=${HOME:=~}
+# <vortex-version>-<df-version>
+CLI_TAG=0.70.0-53.1.0
+WITH_SWAP=false
+
+if [ "$(free -g | awk '/^Mem:/{print $2}')" -lt 12 ]; then
+  echo "LOW MEMORY MODE"
+  if [ "$(swapon --noheadings --show | wc -l)" -eq 0 ]; then
+    echo "Enabling 8G swap"
+    sudo fallocate -l 8G /swapfile
+    sudo chmod 600 /swapfile
+    sudo mkswap /swapfile
+    sudo swapon /swapfile
+    WITH_SWAP=true
+  fi
+fi
+
+echo "Install Rust"
+if ! command -v cargo >/dev/null 2>&1; then
+  curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs > rust-init.sh
+  bash rust-init.sh -y
+fi
+source "$HOME/.cargo/env"
+
+echo "Install dependencies"
+sudo apt-get update -y
+sudo apt-get install -y build-essential cmake pkg-config time
+
+echo "Install vortex-datafusion-cli"
+rm -rf vortex-datafusion-cli
+git clone https://github.com/vortex-data/vortex-datafusion-cli.git
+cd vortex-datafusion-cli
+git checkout "$CLI_TAG"
+CARGO_PROFILE_RELEASE_LTO=true RUSTFLAGS="-C codegen-units=1" cargo build --release --bin vortex-datafusion-cli
+export PATH="$(pwd)/target/release:$PATH"
+cd ..
+
+echo "Download benchmark target data, partitioned"
+mkdir -p partitioned
+seq 0 99 | xargs -P100 -I{} bash -c 'wget --directory-prefix partitioned --continue --progress=dot:giga https://datasets.clickhouse.com/hits_compatible/athena_partitioned/hits_{}.parquet'
+
+echo "Convert Parquet to Vortex"
+rm -rf vortex
+mkdir -p vortex
+if ! /usr/bin/time -f '%e' -o load-time.txt bash -c '
+  set -Eeuo pipefail
+  seq 0 99 | xargs -P"$(nproc)" -I{} ./convert.sh "partitioned/hits_{}.parquet" "vortex/hits_{}.vortex"
+' > convert.log 2>&1; then
+  cat convert.log
+  exit 1
+fi
+VORTEX_FILES=$(find vortex -maxdepth 1 -name 'hits_*.vortex' | wc -l)
+if [ "$VORTEX_FILES" -ne 100 ]; then
+  echo "Expected 100 Vortex files, found $VORTEX_FILES" >&2
+  exit 1
+fi
+echo "Load time: $(cat load-time.txt)"
+
+echo "Run benchmarks for partitioned"
+./run.sh
+
+echo "Data size: $(du -bcs vortex/*.vortex | grep total)"
+
+if [ "$WITH_SWAP" = true ]; then
+    echo "Disable swap"
+    sudo swapoff /swapfile
+    sudo rm /swapfile
+fi

datafusion-vortex-partitioned/convert.sh

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+#!/bin/bash
+
+set -Eeuo pipefail
+
+if [ "$#" -ne 2 ]; then
+  echo "Usage: $0 <input.parquet> <output.vortex>" >&2
+  exit 2
+fi
+
+INPUT=$1
+OUTPUT=$2
+
+mkdir -p "$(dirname "$OUTPUT")"
+rm -f "$OUTPUT"
+
+vortex-datafusion-cli -q \
+  -c "SET datafusion.execution.target_partitions = 1;" \
+  -c "CREATE EXTERNAL TABLE hits_parquet STORED AS PARQUET LOCATION '$INPUT' OPTIONS ('binary_as_string' 'true');" \
+  -c "COPY (SELECT * EXCEPT (\"EventDate\"), CAST(CAST(\"EventDate\" AS INTEGER) AS DATE) AS \"EventDate\" FROM hits_parquet) TO '$OUTPUT' STORED AS VORTEX;"
+
+test -f "$OUTPUT"

datafusion-vortex-partitioned/create.sql

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+CREATE EXTERNAL TABLE hits
+STORED AS VORTEX
+LOCATION 'vortex';

datafusion-vortex-partitioned/make-json.sh

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+#!/bin/bash
+
+# This script converts the raw `result.csv` data from `benchmark.sh` into the
+# final json format used by the benchmark dashboard.
+#
+# usage : ./make-json.sh <machine>
+#
+# example (save results/c6a.4xlarge.json)
+#         ./make-json.sh c6a.4xlarge
+
+MACHINE=$1
+OUTPUT_FILE="results/${MACHINE}.json"
+SYSTEM_NAME="DataFusion (Vortex, partitioned)"
+DATE=$(date +%Y-%m-%d)
+LOAD_TIME=${LOAD_TIME:-$(cat load-time.txt 2>/dev/null || echo null)}
+DATA_SIZE=${DATA_SIZE:-$(du -bcs vortex/*.vortex 2>/dev/null | awk '/total/ { print $1 }')}
+DATA_SIZE=${DATA_SIZE:-null}
+
+mkdir -p results
+
+# Read the CSV and build the result array using sed
+RESULT_ARRAY=$(awk -F, '{arr[$1]=arr[$1]","$3} END {for (i=1;i<=length(arr);i++) {gsub(/^,/, "", arr[i]); printf "        ["arr[i]"]"; if (i<length(arr)) printf ",\n"}}' result.csv)
+
+# form the final JSON structure from the template
+cat <<EOF > $OUTPUT_FILE
+{
+    "system": "$SYSTEM_NAME",
+    "date": "$DATE",
+    "machine": "$MACHINE",
+    "cluster_size": 1,
+    "proprietary": "no",
+    "tuned": "no",
+    "hardware": "cpu",
+    "tags": ["Rust","column-oriented","embedded","stateless"],
+    "load_time": $LOAD_TIME,
+    "data_size": $DATA_SIZE,
+    "result": [
+        $RESULT_ARRAY
+    ]
+}
+EOF

datafusion-vortex-partitioned/queries.sql

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+SELECT COUNT(*) FROM hits;
+SELECT COUNT(*) FROM hits WHERE "AdvEngineID" <> 0;
+SELECT SUM("AdvEngineID"), COUNT(*), AVG("ResolutionWidth") FROM hits;
+SELECT AVG("UserID") FROM hits;
+SELECT COUNT(DISTINCT "UserID") FROM hits;
+SELECT COUNT(DISTINCT "SearchPhrase") FROM hits;
+SELECT MIN("EventDate"), MAX("EventDate") FROM hits;
+SELECT "AdvEngineID", COUNT(*) FROM hits WHERE "AdvEngineID" <> 0 GROUP BY "AdvEngineID" ORDER BY COUNT(*) DESC;
+SELECT "RegionID", COUNT(DISTINCT "UserID") AS u FROM hits GROUP BY "RegionID" ORDER BY u DESC LIMIT 10;
+SELECT "RegionID", SUM("AdvEngineID"), COUNT(*) AS c, AVG("ResolutionWidth"), COUNT(DISTINCT "UserID") FROM hits GROUP BY "RegionID" ORDER BY c DESC LIMIT 10;
+SELECT "MobilePhoneModel", COUNT(DISTINCT "UserID") AS u FROM hits WHERE "MobilePhoneModel" <> '' GROUP BY "MobilePhoneModel" ORDER BY u DESC LIMIT 10;
+SELECT "MobilePhone", "MobilePhoneModel", COUNT(DISTINCT "UserID") AS u FROM hits WHERE "MobilePhoneModel" <> '' GROUP BY "MobilePhone", "MobilePhoneModel" ORDER BY u DESC LIMIT 10;
+SELECT "SearchPhrase", COUNT(*) AS c FROM hits WHERE "SearchPhrase" <> '' GROUP BY "SearchPhrase" ORDER BY c DESC LIMIT 10;
+SELECT "SearchPhrase", COUNT(DISTINCT "UserID") AS u FROM hits WHERE "SearchPhrase" <> '' GROUP BY "SearchPhrase" ORDER BY u DESC LIMIT 10;
+SELECT "SearchEngineID", "SearchPhrase", COUNT(*) AS c FROM hits WHERE "SearchPhrase" <> '' GROUP BY "SearchEngineID", "SearchPhrase" ORDER BY c DESC LIMIT 10;
+SELECT "UserID", COUNT(*) FROM hits GROUP BY "UserID" ORDER BY COUNT(*) DESC LIMIT 10;
+SELECT "UserID", "SearchPhrase", COUNT(*) FROM hits GROUP BY "UserID", "SearchPhrase" ORDER BY COUNT(*) DESC LIMIT 10;
+SELECT "UserID", "SearchPhrase", COUNT(*) FROM hits GROUP BY "UserID", "SearchPhrase" LIMIT 10;
+SELECT "UserID", extract(minute FROM to_timestamp_seconds("EventTime")) AS m, "SearchPhrase", COUNT(*) FROM hits GROUP BY "UserID", m, "SearchPhrase" ORDER BY COUNT(*) DESC LIMIT 10;
+SELECT "UserID" FROM hits WHERE "UserID" = 435090932899640449;
+SELECT COUNT(*) FROM hits WHERE "URL" LIKE '%google%';
+SELECT "SearchPhrase", MIN("URL"), COUNT(*) AS c FROM hits WHERE "URL" LIKE '%google%' AND "SearchPhrase" <> '' GROUP BY "SearchPhrase" ORDER BY c DESC LIMIT 10;
+SELECT "SearchPhrase", MIN("URL"), MIN("Title"), COUNT(*) AS c, COUNT(DISTINCT "UserID") FROM hits WHERE "Title" LIKE '%Google%' AND "URL" NOT LIKE '%.google.%' AND "SearchPhrase" <> '' GROUP BY "SearchPhrase" ORDER BY c DESC LIMIT 10;
+SELECT * FROM hits WHERE "URL" LIKE '%google%' ORDER BY "EventTime" LIMIT 10;
+SELECT "SearchPhrase" FROM hits WHERE "SearchPhrase" <> '' ORDER BY "EventTime" LIMIT 10;
+SELECT "SearchPhrase" FROM hits WHERE "SearchPhrase" <> '' ORDER BY "SearchPhrase" LIMIT 10;
+SELECT "SearchPhrase" FROM hits WHERE "SearchPhrase" <> '' ORDER BY "EventTime", "SearchPhrase" LIMIT 10;
+SELECT "CounterID", AVG(length("URL")) AS l, COUNT(*) AS c FROM hits WHERE "URL" <> '' GROUP BY "CounterID" HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;
+SELECT REGEXP_REPLACE("Referer", '^https?://(?:www\.)?([^/]+)/.*$', '\1') AS k, AVG(length("Referer")) AS l, COUNT(*) AS c, MIN("Referer") FROM hits WHERE "Referer" <> '' GROUP BY k HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;
+SELECT SUM("ResolutionWidth"), SUM("ResolutionWidth" + 1), SUM("ResolutionWidth" + 2), SUM("ResolutionWidth" + 3), SUM("ResolutionWidth" + 4), SUM("ResolutionWidth" + 5), SUM("ResolutionWidth" + 6), SUM("ResolutionWidth" + 7), SUM("ResolutionWidth" + 8), SUM("ResolutionWidth" + 9), SUM("ResolutionWidth" + 10), SUM("ResolutionWidth" + 11), SUM("ResolutionWidth" + 12), SUM("ResolutionWidth" + 13), SUM("ResolutionWidth" + 14), SUM("ResolutionWidth" + 15), SUM("ResolutionWidth" + 16), SUM("ResolutionWidth" + 17), SUM("ResolutionWidth" + 18), SUM("ResolutionWidth" + 19), SUM("ResolutionWidth" + 20), SUM("ResolutionWidth" + 21), SUM("ResolutionWidth" + 22), SUM("ResolutionWidth" + 23), SUM("ResolutionWidth" + 24), SUM("ResolutionWidth" + 25), SUM("ResolutionWidth" + 26), SUM("ResolutionWidth" + 27), SUM("ResolutionWidth" + 28), SUM("ResolutionWidth" + 29), SUM("ResolutionWidth" + 30), SUM("ResolutionWidth" + 31), SUM("ResolutionWidth" + 32), SUM("ResolutionWidth" + 33), SUM("ResolutionWidth" + 34), SUM("ResolutionWidth" + 35), SUM("ResolutionWidth" + 36), SUM("ResolutionWidth" + 37), SUM("ResolutionWidth" + 38), SUM("ResolutionWidth" + 39), SUM("ResolutionWidth" + 40), SUM("ResolutionWidth" + 41), SUM("ResolutionWidth" + 42), SUM("ResolutionWidth" + 43), SUM("ResolutionWidth" + 44), SUM("ResolutionWidth" + 45), SUM("ResolutionWidth" + 46), SUM("ResolutionWidth" + 47), SUM("ResolutionWidth" + 48), SUM("ResolutionWidth" + 49), SUM("ResolutionWidth" + 50), SUM("ResolutionWidth" + 51), SUM("ResolutionWidth" + 52), SUM("ResolutionWidth" + 53), SUM("ResolutionWidth" + 54), SUM("ResolutionWidth" + 55), SUM("ResolutionWidth" + 56), SUM("ResolutionWidth" + 57), SUM("ResolutionWidth" + 58), SUM("ResolutionWidth" + 59), SUM("ResolutionWidth" + 60), SUM("ResolutionWidth" + 61), SUM("ResolutionWidth" + 62), SUM("ResolutionWidth" + 63), SUM("ResolutionWidth" + 64), SUM("ResolutionWidth" + 65), SUM("ResolutionWidth" + 66), SUM("ResolutionWidth" + 67), SUM("ResolutionWidth" + 68), SUM("ResolutionWidth" + 69), SUM("ResolutionWidth" + 70), SUM("ResolutionWidth" + 71), SUM("ResolutionWidth" + 72), SUM("ResolutionWidth" + 73), SUM("ResolutionWidth" + 74), SUM("ResolutionWidth" + 75), SUM("ResolutionWidth" + 76), SUM("ResolutionWidth" + 77), SUM("ResolutionWidth" + 78), SUM("ResolutionWidth" + 79), SUM("ResolutionWidth" + 80), SUM("ResolutionWidth" + 81), SUM("ResolutionWidth" + 82), SUM("ResolutionWidth" + 83), SUM("ResolutionWidth" + 84), SUM("ResolutionWidth" + 85), SUM("ResolutionWidth" + 86), SUM("ResolutionWidth" + 87), SUM("ResolutionWidth" + 88), SUM("ResolutionWidth" + 89) FROM hits;
+SELECT "SearchEngineID", "ClientIP", COUNT(*) AS c, SUM("IsRefresh"), AVG("ResolutionWidth") FROM hits WHERE "SearchPhrase" <> '' GROUP BY "SearchEngineID", "ClientIP" ORDER BY c DESC LIMIT 10;
+SELECT "WatchID", "ClientIP", COUNT(*) AS c, SUM("IsRefresh"), AVG("ResolutionWidth") FROM hits WHERE "SearchPhrase" <> '' GROUP BY "WatchID", "ClientIP" ORDER BY c DESC LIMIT 10;
+SELECT "WatchID", "ClientIP", COUNT(*) AS c, SUM("IsRefresh"), AVG("ResolutionWidth") FROM hits GROUP BY "WatchID", "ClientIP" ORDER BY c DESC LIMIT 10;
+SELECT "URL", COUNT(*) AS c FROM hits GROUP BY "URL" ORDER BY c DESC LIMIT 10;
+SELECT 1, "URL", COUNT(*) AS c FROM hits GROUP BY 1, "URL" ORDER BY c DESC LIMIT 10;
+SELECT "ClientIP", "ClientIP" - 1, "ClientIP" - 2, "ClientIP" - 3, COUNT(*) AS c FROM hits GROUP BY "ClientIP", "ClientIP" - 1, "ClientIP" - 2, "ClientIP" - 3 ORDER BY c DESC LIMIT 10;
+SELECT "URL", COUNT(*) AS PageViews FROM hits WHERE "CounterID" = 62 AND "EventDate" >= '2013-07-01' AND "EventDate" <= '2013-07-31' AND "DontCountHits" = 0 AND "IsRefresh" = 0 AND "URL" <> '' GROUP BY "URL" ORDER BY PageViews DESC LIMIT 10;
+SELECT "Title", COUNT(*) AS PageViews FROM hits WHERE "CounterID" = 62 AND "EventDate" >= '2013-07-01' AND "EventDate" <= '2013-07-31' AND "DontCountHits" = 0 AND "IsRefresh" = 0 AND "Title" <> '' GROUP BY "Title" ORDER BY PageViews DESC LIMIT 10;
+SELECT "URL", COUNT(*) AS PageViews FROM hits WHERE "CounterID" = 62 AND "EventDate" >= '2013-07-01' AND "EventDate" <= '2013-07-31' AND "IsRefresh" = 0 AND "IsLink" <> 0 AND "IsDownload" = 0 GROUP BY "URL" ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;
+SELECT "TraficSourceID", "SearchEngineID", "AdvEngineID", CASE WHEN ("SearchEngineID" = 0 AND "AdvEngineID" = 0) THEN "Referer" ELSE '' END AS Src, "URL" AS Dst, COUNT(*) AS PageViews FROM hits WHERE "CounterID" = 62 AND "EventDate" >= '2013-07-01' AND "EventDate" <= '2013-07-31' AND "IsRefresh" = 0 GROUP BY "TraficSourceID", "SearchEngineID", "AdvEngineID", Src, Dst ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;
+SELECT "URLHash", "EventDate", COUNT(*) AS PageViews FROM hits WHERE "CounterID" = 62 AND "EventDate" >= '2013-07-01' AND "EventDate" <= '2013-07-31' AND "IsRefresh" = 0 AND "TraficSourceID" IN (-1, 6) AND "RefererHash" = 3594120000172545465 GROUP BY "URLHash", "EventDate" ORDER BY PageViews DESC LIMIT 10 OFFSET 100;
+SELECT "WindowClientWidth", "WindowClientHeight", COUNT(*) AS PageViews FROM hits WHERE "CounterID" = 62 AND "EventDate" >= '2013-07-01' AND "EventDate" <= '2013-07-31' AND "IsRefresh" = 0 AND "DontCountHits" = 0 AND "URLHash" = 2868770270353813622 GROUP BY "WindowClientWidth", "WindowClientHeight" ORDER BY PageViews DESC LIMIT 10 OFFSET 10000;
+SELECT DATE_TRUNC('minute', to_timestamp_seconds("EventTime")) AS M, COUNT(*) AS PageViews FROM hits WHERE "CounterID" = 62 AND "EventDate" >= '2013-07-14' AND "EventDate" <= '2013-07-15' AND "IsRefresh" = 0 AND "DontCountHits" = 0 GROUP BY DATE_TRUNC('minute', to_timestamp_seconds("EventTime")) ORDER BY DATE_TRUNC('minute', M) LIMIT 10 OFFSET 1000;

datafusion-vortex-partitioned/results/c6a.2xlarge.json

@@ -0,0 +1,57 @@
+{
+    "system": "DataFusion (Vortex, partitioned)",
+    "date": "2026-05-05",
+    "machine": "c6a.2xlarge",
+    "cluster_size": 1,
+    "proprietary": "no",
+    "tuned": "no",
+    "hardware": "cpu",
+    "tags": ["Rust","column-oriented","embedded","stateless"],
+    "load_time": 108.58,
+    "data_size": 15328662856,
+    "result": [
+        [0.078,0.002,0.002],
+        [0.170,0.027,0.028],
+        [0.214,0.072,0.069],
+        [0.650,0.071,0.070],
+        [1.367,0.840,0.837],
+        [1.355,0.785,0.786],
+        [0.075,0.002,0.002],
+        [0.179,0.031,0.033],
+        [1.269,1.045,1.044],
+        [1.670,1.251,1.237],
+        [0.770,0.162,0.156],
+        [1.099,0.192,0.191],
+        [1.603,0.694,0.682],
+        [3.280,1.199,1.198],
+        [1.395,0.667,0.670],
+        [1.108,0.948,0.942],
+        [3.158,1.772,1.779],
+        [3.122,1.778,1.785],
+        [5.120,3.531,3.507],
+        [0.313,0.043,0.048],
+        [15.675,0.906,0.901],
+        [17.831,0.929,0.926],
+        [22.767,1.105,1.103],
+        [22.582,1.521,1.574],
+        [0.319,0.079,0.075],
+        [1.603,0.146,0.147],
+        [0.609,0.081,0.082],
+        [16.343,1.328,1.365],
+        [15.637,15.200,15.211],
+        [0.814,0.656,0.668],
+        [2.796,0.592,0.595],
+        [5.885,0.641,0.629],
+        [3.929,3.007,3.019],
+        [16.025,3.545,3.512],
+        [15.999,3.567,3.503],
+        [1.455,1.293,1.298],
+        [0.254,0.074,0.073],
+        [0.203,0.034,0.034],
+        [0.243,0.024,0.022],
+        [0.386,0.130,0.129],
+        [0.247,0.019,0.016],
+        [0.249,0.015,0.015],
+        [0.242,0.014,0.015]
+    ]
+}

datafusion-vortex-partitioned/results/c6a.4xlarge.json

@@ -0,0 +1,57 @@
+{
+    "system": "DataFusion (Vortex, partitioned)",
+    "date": "2026-05-05",
+    "machine": "c6a.4xlarge",
+    "cluster_size": 1,
+    "proprietary": "no",
+    "hardware": "cpu",
+    "tuned": "no",
+    "tags": ["Rust","column-oriented","embedded","stateless"],
+    "load_time": 99.94,
+    "data_size": 15328662856,
+    "result": [
+        [0.082, 0.002, 0.002],
+        [0.152, 0.030, 0.027],
+        [0.175, 0.059, 0.060],
+        [0.633, 0.087, 0.089],
+        [1.306, 0.628, 0.626],
+        [1.316, 0.603, 0.592],
+        [0.090, 0.002, 0.002],
+        [0.166, 0.031, 0.030],
+        [1.223, 0.786, 0.772],
+        [1.664, 0.861, 0.871],
+        [0.729, 0.131, 0.133],
+        [1.116, 0.148, 0.147],
+        [1.605, 0.581, 0.578],
+        [3.174, 1.070, 1.068],
+        [1.527, 0.610, 0.597],
+        [0.887, 0.727, 0.715],
+        [3.174, 1.509, 1.532],
+        [3.153, 1.510, 1.506],
+        [4.788, 2.907, 2.827],
+        [0.313, 0.048, 0.049],
+        [15.848, 0.537, 0.528],
+        [17.859, 0.781, 0.772],
+        [22.900, 0.894, 0.878],
+        [21.132, 0.858, 0.785],
+        [0.287, 0.084, 0.091],
+        [1.607, 0.153, 0.146],
+        [0.757, 0.088, 0.088],
+        [16.230, 0.974, 1.011],
+        [13.690, 8.122, 8.151],
+        [0.512, 0.369, 0.364],
+        [2.788, 0.487, 0.487],
+        [5.882, 0.592, 0.589],
+        [3.929, 2.653, 2.674],
+        [15.934, 3.107, 2.890],
+        [15.951, 2.902, 2.918],
+        [1.060, 0.930, 0.917],
+        [0.261, 0.082, 0.082],
+        [0.208, 0.035, 0.036],
+        [0.197, 0.024, 0.023],
+        [0.385, 0.146, 0.146],
+        [0.251, 0.017, 0.016],
+        [0.248, 0.019, 0.014],
+        [0.244, 0.015, 0.015]
+    ]
+}