feat(arc): add ClickBench results for Arc on c6a.4xlarge

arc/benchmark.sh

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+#!/bin/bash
+# Arc ClickBench Complete Benchmark Script
+# This script installs Arc, loads data, and runs the benchmark
+
+set -e
+
+# Install Python and dependencies
+echo "Installing dependencies..."
+pip3 install duckdb requests
+
+# Download and prepare dataset
+echo "Downloading ClickBench dataset..."
+wget --continue 'https://datasets.clickhouse.com/hits_compatible/hits.parquet'
+
+echo "Dataset size:"
+ls -lh hits.parquet
+
+# Count rows
+echo "Counting rows..."
+python3 << 'EOF'
+import duckdb
+conn = duckdb.connect()
+count = conn.execute("SELECT COUNT(*) FROM read_parquet('hits.parquet')").fetchone()[0]
+print(f"Dataset rows: {count:,}")
+EOF
+
+# Run benchmark
+echo "Running ClickBench queries..."
+./run.sh 2>&1 | tee log.txt
+
+# Format results
+echo "Formatting results..."
+cat log.txt | \
+  grep -E '^\d+\.\d+|null' | \
+  awk 'BEGIN {print "["}
+       {
+         if (NR % 3 == 1) printf "  [";
+         printf "%s", $1;
+         if (NR % 3 == 0) print "],";
+         else printf ", ";
+       }
+       END {print "]"}'
+
+echo "Benchmark complete!"

arc/create.sql

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+-- Arc uses DuckDB to query Parquet files directly
+-- Schema is inferred from the Parquet file structure
+-- This file documents the schema for reference
+
+CREATE TABLE hits
+(
+    WatchID BIGINT NOT NULL,
+    JavaEnable SMALLINT NOT NULL,
+    Title TEXT,
+    GoodEvent SMALLINT NOT NULL,
+    EventTime TIMESTAMP NOT NULL,
+    EventDate Date NOT NULL,
+    CounterID INTEGER NOT NULL,
+    ClientIP INTEGER NOT NULL,
+    RegionID INTEGER NOT NULL,
+    UserID BIGINT NOT NULL,
+    CounterClass SMALLINT NOT NULL,
+    OS SMALLINT NOT NULL,
+    UserAgent SMALLINT NOT NULL,
+    URL TEXT,
+    Referer TEXT,
+    IsRefresh SMALLINT NOT NULL,
+    RefererCategoryID SMALLINT NOT NULL,
+    RefererRegionID INTEGER NOT NULL,
+    URLCategoryID SMALLINT NOT NULL,
+    URLRegionID INTEGER NOT NULL,
+    ResolutionWidth SMALLINT NOT NULL,
+    ResolutionHeight SMALLINT NOT NULL,
+    ResolutionDepth SMALLINT NOT NULL,
+    FlashMajor SMALLINT NOT NULL,
+    FlashMinor SMALLINT NOT NULL,
+    FlashMinor2 TEXT,
+    NetMajor SMALLINT NOT NULL,
+    NetMinor SMALLINT NOT NULL,
+    UserAgentMajor SMALLINT NOT NULL,
+    UserAgentMinor VARCHAR(255) NOT NULL,
+    CookieEnable SMALLINT NOT NULL,
+    JavascriptEnable SMALLINT NOT NULL,
+    IsMobile SMALLINT NOT NULL,
+    MobilePhone SMALLINT NOT NULL,
+    MobilePhoneModel TEXT,
+    Params TEXT,
+    IPNetworkID INTEGER NOT NULL,
+    TraficSourceID SMALLINT NOT NULL,
+    SearchEngineID SMALLINT NOT NULL,
+    SearchPhrase TEXT,
+    AdvEngineID SMALLINT NOT NULL,
+    IsArtifical SMALLINT NOT NULL,
+    WindowClientWidth SMALLINT NOT NULL,
+    WindowClientHeight SMALLINT NOT NULL,
+    ClientTimeZone SMALLINT NOT NULL,
+    ClientEventTime TIMESTAMP NOT NULL,
+    SilverlightVersion1 SMALLINT NOT NULL,
+    SilverlightVersion2 SMALLINT NOT NULL,
+    SilverlightVersion3 INTEGER NOT NULL,
+    SilverlightVersion4 SMALLINT NOT NULL,
+    PageCharset TEXT,
+    CodeVersion INTEGER NOT NULL,
+    IsLink SMALLINT NOT NULL,
+    IsDownload SMALLINT NOT NULL,
+    IsNotBounce SMALLINT NOT NULL,
+    FUniqID BIGINT NOT NULL,
+    OriginalURL TEXT,
+    HID INTEGER NOT NULL,
+    IsOldCounter SMALLINT NOT NULL,
+    IsEvent SMALLINT NOT NULL,
+    IsParameter SMALLINT NOT NULL,
+    DontCountHits SMALLINT NOT NULL,
+    WithHash SMALLINT NOT NULL,
+    HitColor CHAR NOT NULL,
+    LocalEventTime TIMESTAMP NOT NULL,
+    Age SMALLINT NOT NULL,
+    Sex SMALLINT NOT NULL,
+    Income SMALLINT NOT NULL,
+    Interests SMALLINT NOT NULL,
+    Robotness SMALLINT NOT NULL,
+    RemoteIP INTEGER NOT NULL,
+    WindowName INTEGER NOT NULL,
+    OpenerName INTEGER NOT NULL,
+    HistoryLength SMALLINT NOT NULL,
+    BrowserLanguage TEXT,
+    BrowserCountry TEXT,
+    SocialNetwork TEXT,
+    SocialAction TEXT,
+    HTTPError SMALLINT NOT NULL,
+    SendTiming INTEGER NOT NULL,
+    DNSTiming INTEGER NOT NULL,
+    ConnectTiming INTEGER NOT NULL,
+    ResponseStartTiming INTEGER NOT NULL,
+    ResponseEndTiming INTEGER NOT NULL,
+    FetchTiming INTEGER NOT NULL,
+    SocialSourceNetworkID SMALLINT NOT NULL,
+    SocialSourcePage TEXT,
+    ParamPrice BIGINT NOT NULL,
+    ParamOrderID TEXT,
+    ParamCurrency TEXT,
+    ParamCurrencyID SMALLINT NOT NULL,
+    OpenstatServiceName TEXT,
+    OpenstatCampaignID TEXT,
+    OpenstatAdID TEXT,
+    OpenstatSourceID TEXT,
+    UTMSource TEXT,
+    UTMMedium TEXT,
+    UTMCampaign TEXT,
+    UTMContent TEXT,
+    UTMTerm TEXT,
+    FromTag TEXT,
+    HasGCLID SMALLINT NOT NULL,
+    RefererHash BIGINT NOT NULL,
+    URLHash BIGINT NOT NULL,
+    CLID INTEGER NOT NULL
+);

arc/queries.sql

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+-- ClickBench Queries for Arc
+-- Original: https://github.com/ClickHouse/ClickBench
+-- Adapted for Arc's DuckDB engine (table name: clickbench.hits)
+
+SELECT COUNT(*) FROM clickbench.hits;
+SELECT COUNT(*) FROM clickbench.hits WHERE AdvEngineID <> 0;
+SELECT SUM(AdvEngineID), COUNT(*), AVG(ResolutionWidth) FROM clickbench.hits;
+SELECT AVG(UserID) FROM clickbench.hits;
+SELECT COUNT(DISTINCT UserID) FROM clickbench.hits;
+SELECT COUNT(DISTINCT SearchPhrase) FROM clickbench.hits;
+SELECT MIN(EventDate), MAX(EventDate) FROM clickbench.hits;
+SELECT AdvEngineID, COUNT(*) FROM clickbench.hits WHERE AdvEngineID <> 0 GROUP BY AdvEngineID ORDER BY COUNT(*) DESC;
+SELECT RegionID, COUNT(DISTINCT UserID) AS u FROM clickbench.hits GROUP BY RegionID ORDER BY u DESC LIMIT 10;
+SELECT RegionID, SUM(AdvEngineID), COUNT(*) AS c, AVG(ResolutionWidth), COUNT(DISTINCT UserID) FROM clickbench.hits GROUP BY RegionID ORDER BY c DESC LIMIT 10;
+SELECT MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM clickbench.hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10;
+SELECT MobilePhone, MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM clickbench.hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10;
+SELECT SearchPhrase, COUNT(*) AS c FROM clickbench.hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;
+SELECT SearchPhrase, COUNT(DISTINCT UserID) AS u FROM clickbench.hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10;
+SELECT SearchEngineID, SearchPhrase, COUNT(*) AS c FROM clickbench.hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10;
+SELECT UserID, COUNT(*) FROM clickbench.hits GROUP BY UserID ORDER BY COUNT(*) DESC LIMIT 10;
+SELECT UserID, SearchPhrase, COUNT(*) FROM clickbench.hits GROUP BY UserID, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;
+SELECT UserID, SearchPhrase, COUNT(*) FROM clickbench.hits GROUP BY UserID, SearchPhrase LIMIT 10;
+SELECT UserID, extract(minute FROM CAST(to_timestamp(EventTime) AS TIMESTAMP)) AS m, SearchPhrase, COUNT(*) FROM clickbench.hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;
+SELECT UserID FROM clickbench.hits WHERE UserID = 435090932899640449;
+SELECT COUNT(*) FROM clickbench.hits WHERE URL LIKE '%google%';
+SELECT SearchPhrase, MIN(URL), COUNT(*) AS c FROM clickbench.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 clickbench.hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.google.%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;
+SELECT * FROM clickbench.hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMIT 10;
+SELECT SearchPhrase FROM clickbench.hits WHERE SearchPhrase <> '' ORDER BY EventTime LIMIT 10;
+SELECT SearchPhrase FROM clickbench.hits WHERE SearchPhrase <> '' ORDER BY SearchPhrase LIMIT 10;
+SELECT SearchPhrase FROM clickbench.hits WHERE SearchPhrase <> '' ORDER BY EventTime, SearchPhrase LIMIT 10;
+SELECT CounterID, AVG(length(URL)) AS l, COUNT(*) AS c FROM clickbench.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 clickbench.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 clickbench.hits;
+SELECT SearchEngineID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM clickbench.hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10;
+SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM clickbench.hits WHERE SearchPhrase <> '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;
+SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM clickbench.hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;
+SELECT URL, COUNT(*) AS c FROM clickbench.hits GROUP BY URL ORDER BY c DESC LIMIT 10;
+SELECT 1, URL, COUNT(*) AS c FROM clickbench.hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10;
+SELECT ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3, COUNT(*) AS c FROM clickbench.hits GROUP BY ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3 ORDER BY c DESC LIMIT 10;
+SELECT URL, COUNT(*) AS PageViews FROM clickbench.hits WHERE CounterID = 62 AND EventDate >= 15887 AND EventDate <= 15917 AND DontCountHits = 0 AND IsRefresh = 0 AND URL <> '' GROUP BY URL ORDER BY PageViews DESC LIMIT 10;
+SELECT Title, COUNT(*) AS PageViews FROM clickbench.hits WHERE CounterID = 62 AND EventDate >= 15887 AND EventDate <= 15917 AND DontCountHits = 0 AND IsRefresh = 0 AND Title <> '' GROUP BY Title ORDER BY PageViews DESC LIMIT 10;
+SELECT URL, COUNT(*) AS PageViews FROM clickbench.hits WHERE CounterID = 62 AND EventDate >= 15887 AND EventDate <= 15917 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 clickbench.hits WHERE CounterID = 62 AND EventDate >= 15887 AND EventDate <= 15917 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 clickbench.hits WHERE CounterID = 62 AND EventDate >= 15887 AND EventDate <= 15917 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 clickbench.hits WHERE CounterID = 62 AND EventDate >= 15887 AND EventDate <= 15917 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', CAST(to_timestamp(EventTime) AS TIMESTAMP)) AS M, COUNT(*) AS PageViews FROM clickbench.hits WHERE CounterID = 62 AND EventDate >= 15900 AND EventDate <= 15901 AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', CAST(to_timestamp(EventTime) AS TIMESTAMP)) ORDER BY DATE_TRUNC('minute', CAST(to_timestamp(EventTime) AS TIMESTAMP)) LIMIT 10 OFFSET 1000;

arc/results/c6a.4xlarge.json

@@ -0,0 +1,62 @@
+{
+  "system": "Arc",
+  "date": "2025-10-06",
+  "machine": "c6a.4xlarge",
+  "cluster_size": 1,
+  "proprietary": "no",
+  "tuned": "no",
+  "tags": [
+    "Python",
+    "time-series",
+    "DuckDB",
+    "Parquet",
+    "columnar"
+  ],
+  "load_time": null,
+  "data_size": 14000000000,
+  "result": [
+    [0.0629, 0.0598, 0.0608],
+    [0.0846, 0.0847, 0.0870],
+    [0.0886, 0.0850, 0.0869],
+    [0.3330, 0.3097, 0.3117],
+    [0.5360, 0.5253, 0.5369],
+    [0.0719, 0.0667, 0.0683],
+    [0.0707, 0.0639, 0.0664],
+    [0.4331, 0.4264, 0.4353],
+    [0.5384, 0.5285, 0.5439],
+    [0.1479, 0.1467, 0.1504],
+    [0.1673, 0.1661, 0.1702],
+    [0.5553, 0.5317, 0.5478],
+    [0.8851, 0.8675, 0.8841],
+    [0.6008, 0.5933, 0.5953],
+    [0.3836, 0.3883, 0.3997],
+    [1.0420, 1.0142, 1.0319],
+    [0.7809, 0.7817, 0.7917],
+    [4.0727, 4.0546, 4.0838],
+    [0.0785, 0.0657, 0.0713],
+    [0.9383, 0.9126, 0.9463],
+    [0.8508, 0.8467, 0.8630],
+    [1.7010, 1.6834, 1.6993],
+    [0.4882, 0.5006, 0.5127],
+    [0.2008, 0.1981, 0.2025],
+    [0.3001, 0.2953, 0.3082],
+    [0.1578, 0.1428, 0.1532],
+    [1.0059, 0.9957, 1.0063],
+    [8.9958, 8.9663, 9.0972],
+    [0.0864, 0.0836, 0.0895],
+    [0.5734, 0.5647, 0.5789],
+    [0.6826, 0.6796, 0.6868],
+    [2.0105, 1.9684, 2.0174],
+    [2.3311, 2.3487, 2.3659],
+    [2.4429, 2.4123, 2.4523],
+    [0.5371, 0.5371, 0.5749],
+    [0.1468, 0.1520, 0.1659],
+    [0.1236, 0.1239, 0.1307],
+    [0.1006, 0.0944, 0.0969],
+    [0.2723, 0.2529, 0.2566],
+    [0.0663, 0.0685, 0.0730],
+    [0.0676, 0.0631, 0.0659],
+    [0.1677, 0.1708, 0.1898],
+    [0.1378, 0.1370, 0.1500]
+  ]
+}

arc/results/m3_max.json

@@ -0,0 +1,62 @@
+{
+  "system": "Arc",
+  "date": "2025-10-05",
+  "machine": "m3_max",
+  "cluster_size": 1,
+  "proprietary": "no",
+  "tuned": "no",
+  "tags": [
+    "Python",
+    "time-series",
+    "DuckDB",
+    "Parquet",
+    "columnar"
+  ],
+  "load_time": null,
+  "data_size": 14000000000,
+  "result": [
+    [0.0420, 0.0403, 0.0804],
+    [0.0623, 0.0558, 0.0601],
+    [0.0775, 0.0634, 0.0644],
+    [0.2134, 0.2150, 0.2183],
+    [0.2833, 0.2864, 0.2914],
+    [0.0486, 0.0470, 0.0491],
+    [0.0446, 0.0421, 0.0443],
+    [0.2822, 0.2661, 0.2739],
+    [0.3496, 0.3433, 0.3483],
+    [0.1016, 0.0995, 0.1058],
+    [0.1242, 0.1121, 0.1200],
+    [0.2946, 0.2923, 0.3035],
+    [0.5051, 0.4858, 0.5037],
+    [0.3370, 0.3467, 0.3785],
+    [0.2549, 0.2513, 0.2640],
+    [0.7513, 0.6500, 0.7538],
+    [0.5833, 0.5640, 0.5757],
+    [1.8692, 1.8193, 1.8426],
+    [0.0692, 0.0749, 0.0764],
+    [0.8728, 0.6665, 0.6845],
+    [0.5656, 0.5566, 0.5897],
+    [1.1862, 1.1310, 1.1831],
+    [0.3373, 0.3221, 0.3284],
+    [0.1317, 0.1342, 0.1368],
+    [0.1968, 0.1941, 0.1949],
+    [0.0918, 0.0956, 0.1025],
+    [0.7141, 0.6861, 0.7442],
+    [8.3151, 8.0191, 8.0986],
+    [0.0824, 0.0756, 0.0810],
+    [0.3594, 0.3357, 0.3442],
+    [0.3840, 0.3830, 0.3946],
+    [2.1044, 1.0679, 1.2545],
+    [1.1666, 1.1622, 1.2095],
+    [1.1709, 1.1823, 1.2135],
+    [0.3138, 0.3118, 0.3147],
+    [0.0887, 0.0887, 0.0894],
+    [0.0922, 0.0896, 0.0918],
+    [0.0654, 0.0630, 0.0691],
+    [0.1427, 0.1444, 0.1499],
+    [0.0514, 0.0450, 0.0498],
+    [0.0480, 0.0453, 0.0473],
+    [0.0947, 0.0879, 0.0925],
+    [0.0877, 0.0872, 0.0955]
+  ]
+}

arc/run.sh

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+#!/bin/bash
+# Arc ClickBench Benchmark Runner
+# This script was used to generate the benchmark results
+
+TRIES=3
+PARQUET_FILE="hits.parquet"
+
+python3 << 'EOF'
+import duckdb
+import time
+import multiprocessing
+from pathlib import Path
+
+PARQUET_FILE = Path("hits.parquet")
+
+# Connect to DuckDB
+conn = duckdb.connect()
+
+# Configure optimizations
+cpu_count = multiprocessing.cpu_count()
+conn.execute(f"SET threads TO {cpu_count}")
+conn.execute("SET enable_object_cache TO true")
+
+# Create view from parquet
+conn.execute(f"CREATE SCHEMA IF NOT EXISTS clickbench")
+conn.execute(f"CREATE VIEW clickbench.hits AS SELECT * FROM read_parquet('{PARQUET_FILE}')")
+
+# Read queries
+with open('queries.sql') as f:
+    content = f.read()
+
+queries = []
+for query in content.split(';'):
+    query = query.strip()
+    if query and not query.startswith('--'):
+        queries.append(query)
+
+# Run each query 3 times
+for i, query_sql in enumerate(queries, 1):
+    for run in range(3):
+        try:
+            start = time.perf_counter()
+            conn.execute(query_sql).fetchall()
+            elapsed = time.perf_counter() - start
+            print(f"{elapsed:.4f}")
+        except Exception as e:
+            print("null")
+EOF

arc/template.json

@@ -0,0 +1,6 @@
+{
+  "system": "Arc",
+  "proprietary": "no",
+  "tuned": "no",
+  "tags": ["Python", "time-series", "DuckDB", "Parquet", "columnar"]
+}