add Apache Comet

spark-comet/README.md

@@ -0,0 +1,27 @@
+This README includes info on configuring Comet for ClickBench. For additional details, please refer to [Comet's docs](https://datafusion.apache.org/comet/user-guide/overview.html), [spark-accelerators README](../spark/README-accelerators.md) and [issue](https://github.com/apache/datafusion-comet/issues/2035) discussing the results.
+
+### Run
+
+As usual, benchmark can be run via `./benchmark.sh`. Additionally, users can provide machine spec like `./benchmark.sh c6a.8xlarge` so script saves it in relevant file.
+
+### Tips
+- To find all unsupported queries from `log.txt` (requires running bench in debug mode):
+```bash
+>>> grep -P "\[COMET:" log.txt | sed -e 's/^[ \t]*//' | sort | uniq -c
+
+     78 +-  GlobalLimit [COMET: GlobalLimit is not supported]
+     18 +-  HashAggregate [COMET: Unsupported aggregation mode PartialMerge]
+    123 +-  HashAggregate [COMET: distinct aggregates are not supported]
+    ...
+```
+- Check [here](https://datafusion.apache.org/comet/user-guide/installation.html#supported-spark-versions) for _version compatibility_ between Spark and Comet.
+- Check [here](https://datafusion.apache.org/comet/user-guide/installation.html#using-a-published-jar-file) for _links to Comet jar_.
+- Check [here](https://datafusion.apache.org/comet/user-guide/installation.html#run-spark-shell-with-comet-enabled) for _basic Comet configuration_.
+
+### Configuration
+- Comet requires a __dedicated memory pool__, which can be allocated either through memoryOverhead or off-heap memory. The [documentation recommends](https://datafusion.apache.org/comet/user-guide/tuning.html#configuring-comet-memory-in-off-heap-mode) using off-heap memory, which is the approach used in ClickBench.
+Therefore, we need to split available memory between heap (for Spark) and off-heap (for Comet). For both TPC-H and TPC-DS benchmarks, Comet documentation [suggests](https://datafusion.apache.org/comet/contributor-guide/benchmarking.html) a 50/50 split. This allocation appears to be chosen to support Spark execution as well — it happens when Comet can't handle certain operators, which is also relevant for ClickBench.
+- `spark.driver.extraClassPath` is set to prevent Comet from failing on certain queries (check [docs](https://datafusion.apache.org/comet/user-guide/installation.html#additional-configuration) for details).
+- `spark.comet.regexp.allowIncompatible=True` allows Comet to use incompatible regular expressions instead of falling back to Spark (check [docs](https://datafusion.apache.org/comet/user-guide/compatibility.html#regular-expressions) for details).
+- `spark.comet.scan.allowIncompatible=True` allows Comet to use different parquet readers to prevent query failures (check [issue](https://github.com/apache/datafusion-comet/issues/2035#issuecomment-3090666597) for details). <br>
+What happens here: `hits.parquet` contains `short` type columns, so Comet uses the `native_comet` reader for compatibility. However, this reader [doesn't work](https://github.com/apache/datafusion-comet/issues/2038) for some queries (e.g., query 40), causing Comet to fail. As a workaround, we can allow Comet to produce results incompatible with Spark, enabling it to use [other readers](https://datafusion.apache.org/comet/user-guide/compatibility.html#parquet-scans) and successfully execute these queries.

spark-comet/benchmark.sh

@@ -0,0 +1,90 @@
+#!/bin/bash
+
+# Note: Keep in sync with spark-*/benchmark.sh (see README-accelerators.md for details)
+#
+# Current differences:
+# - pyspark==3.5.6 version is used (latest stable for Comet 0.9.0)
+# - Comet installation is added
+# - auto-save results
+
+# Install
+
+sudo apt-get update -y
+sudo apt-get install -y python3-pip python3-venv openjdk-17-jdk
+
+export JAVA_HOME="/usr/lib/jvm/java-17-openjdk-$(dpkg --print-architecture)/"
+export PATH=$JAVA_HOME/bin:$PATH
+
+python3 -m venv myenv
+source myenv/bin/activate
+pip install pyspark==3.5.6 psutil
+
+# Load the data
+
+wget --continue --progress=dot:giga 'https://datasets.clickhouse.com/hits_compatible/hits.parquet'
+
+# Install Comet
+
+COMET_JAR_URL='https://repo1.maven.org/maven2/org/apache/datafusion/comet-spark-spark3.5_2.12/0.9.0/comet-spark-spark3.5_2.12-0.9.0.jar'
+
+wget --continue --progress=dot:giga $COMET_JAR_URL -O comet.jar
+
+# Run the queries
+
+./run.sh 2>&1 | tee log.txt
+
+# Print results to stdout as required
+cat log.txt | grep -P '^Time:\s+([\d\.]+)|Failure!' | sed -r -e 's/Time: //; s/^Failure!$/null/' |
+    awk '{ if (i % 3 == 0) { printf "[" }; printf $1; if (i % 3 != 2) { printf "," } else { print "]," }; ++i; }'
+
+DATA_SIZE=$(du -b hits.parquet | cut -f1)
+
+echo "Data size: $DATA_SIZE"
+echo "Load time: 0"
+
+# Save results as JSON
+
+MACHINE="${1:-c6a.4xlarge}"  # Use first argument as machine name, default to c6a.4xlarge
+COMET_VERSION=$(echo $COMET_JAR_URL | grep -Po ".{5}(?=.jar)")
+SPARK_VERSION=$(pip freeze | grep '^pyspark==' | cut -d '=' -f3)
+
+mkdir -p results
+
+(
+cat << EOF
+{
+    "system": "Spark (Comet)",
+    "date": "$(date +%Y-%m-%d)",
+    "machine": "${MACHINE}",
+    "cluster_size": 1,
+    "proprietary": "no",
+    "tuned": "no",
+    "comment": "Using Comet ${COMET_VERSION} with Spark ${SPARK_VERSION}",
+    "tags": ["Java", "Rust", "column-oriented", "Spark derivative", "DataFusion", "Parquet"],
+    "load_time": 0,
+    "data_size": ${DATA_SIZE},
+    "result": [
+EOF
+
+cat log.txt | grep -P '^Time:\s+([\d\.]+)|Failure!' | sed -r -e 's/Time: //; s/^Failure!$/null/' |
+    awk -v total=$(grep -cP '^Time:\s+[\d\.]+|Failure!' log.txt) '
+        {
+            if (i % 3 == 0) printf "\t\t[";
+                if ($1 == "null") printf "null";
+                else printf "%.3f", $1;
+            if (i % 3 != 2) printf ", ";
+            else {
+                if (i < total - 1) printf "],\n";
+                else printf "]";
+            }
+            i++;
+        }'
+
+cat << EOF
+
+    ]
+}
+EOF
+) > "results/${MACHINE}.json"
+
+echo "Results have been saved to results/${MACHINE}.json"

spark-comet/queries.sql

@@ -0,0 +1,43 @@
+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 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', 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', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000;

spark-comet/query.py

@@ -0,0 +1,74 @@
+#!/usr/bin/env python3
+
+"""
+Note: Keep in sync with spark-*/query.py (see README-accelerators.md for details)
+
+Current differences:
+- memory is split between heap (for Spark) and off-heap (for Comet)
+- Comet configuration is added to `SparkSession`
+- debug mode is added
+"""
+
+from pyspark.sql import SparkSession
+import pyspark.sql.functions as F
+
+import os
+import psutil
+import re
+import sys
+import timeit
+
+
+query = sys.stdin.read()
+# Replace \1 to $1 because spark recognizes only this pattern style (in query 28)
+query = re.sub(r"""(REGEXP_REPLACE\(.*?,\s*('[^']*')\s*,\s*)('1')""", r"\1'$1'", query)
+print(query)
+
+# Calculate available memory to configurate SparkSession
+ram = int(round(psutil.virtual_memory().available / (1024 ** 3) * 0.7))
+heap = ram // 2
+off_heap = ram - heap
+print(f"SparkSession will use {heap} GB of heap and {off_heap} GB of off-heap memory")
+
+builder = (
+    SparkSession
+    .builder
+    .appName("ClickBench")
+    .config("spark.driver", "local[*]") # To ensure using all cores
+    .config("spark.driver.memory", f"{heap}g") # Set amount of memory SparkSession can use
+    .config("spark.sql.parquet.binaryAsString", True) # Treat binary as string to get correct length calculations and text results
+
+    # Additional Comet configuration
+    .config("spark.jars", "comet.jar")
+    .config("spark.driver.extraClassPath", "comet.jar")
+    .config("spark.plugins", "org.apache.spark.CometPlugin")
+    .config("spark.shuffle.manager", "org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager")
+    .config("spark.memory.offHeap.enabled", "true")
+    .config("spark.memory.offHeap.size", f"{off_heap}g")
+    .config("spark.comet.regexp.allowIncompatible", True)
+    .config("spark.comet.scan.allowIncompatible", True)
+)
+
+# Even more Comet configuration
+if os.getenv("DEBUG") == "1":
+    builder.config("spark.comet.explainFallback.enabled", "true")
+    builder.config("spark.sql.debug.maxToStringFields", "10000")
+
+spark = builder.getOrCreate()
+
+df = spark.read.parquet("hits.parquet")
+# Do casting before creating the view so no need to change to unreadable integer dates in SQL
+df = df.withColumn("EventTime", F.col("EventTime").cast("timestamp"))
+df = df.withColumn("EventDate", F.date_add(F.lit("1970-01-01"), F.col("EventDate")))
+df.createOrReplaceTempView("hits")
+
+for try_num in range(3):
+    try:
+        start = timeit.default_timer()
+        result = spark.sql(query)
+        result.show(100) # some queries should return more than 20 rows which is the default show limit
+        end = timeit.default_timer()
+        print("Time: ", end - start)
+    except Exception as e:
+        print(e)
+        print("Failure!")

spark-comet/results/c6a.4xlarge.json

@@ -0,0 +1,57 @@
+{
+    "system": "Spark (Comet)",
+    "date": "2025-07-17",
+    "machine": "c6a.4xlarge",
+    "cluster_size": 1,
+    "proprietary": "no",
+    "tuned": "no",
+    "comment": "Using Comet 0.9.0 with Spark 3.5.6",
+    "tags": ["Java", "Rust", "column-oriented", "Spark derivative", "DataFusion", "Parquet"],
+    "load_time": 0,
+    "data_size": 14779976446,
+    "result": [
+        [4.472, 2.103, 1.843],
+        [3.578, 1.073, 0.934],
+        [6.644, 1.412, 1.175],
+        [4.696, 2.004, 1.786],
+        [5.631, 2.619, 2.494],
+        [6.264, 2.870, 2.715],
+        [5.0163, 2.275, 2.116],
+        [3.756, 1.121, 0.928],
+        [6.773, 2.983, 2.714],
+        [13.568, 4.030, 3.534],
+        [5.836, 2.355, 2.186],
+        [5.648, 1.566, 1.407],
+        [6.183, 3.122, 2.780],
+        [10.864, 5.143, 4.993],
+        [5.930, 2.934, 2.704],
+        [5.991, 3.144, 2.790],
+        [8.383, 4.513, 4.088],
+        [7.609, 3.542, 3.492],
+        [16.285, 12.08, 11.858],
+        [4.626, 2.276, 2.057],
+        [21.794, 3.180, 3.069],
+        [25.802, 3.617, 3.358],
+        [47.731, 5.476, 5.387],
+        [112.794, 20.449, 20.447],
+        [8.229, 2.295, 2.258],
+        [5.093, 2.193, 2.009],
+        [8.189, 2.316, 2.309],
+        [22.221, 3.847, 3.526],
+        [24.937, 17.818, 17.447],
+        [6.512, 3.486, 3.336],
+        [11.685, 2.552, 2.231],
+        [21.547, 3.102, 2.872],
+        [18.465, 8.194, 7.955],
+        [24.087, 8.077, 7.767],
+        [24.110, 8.102, 7.702],
+        [6.394, 3.394, 3.071],
+        [32.970, 4.560, 4.352],
+        [26.427, 4.248, 4.169],
+        [37.740, 4.908, 4.685],
+        [null, null, null],
+        [13.638, 1.867, 1.490],
+        [25.261, 2.015, 1.763],
+        [8.614, 1.839, 1.526]
+    ]
+}

spark-comet/run.sh

@@ -0,0 +1,10 @@
+#!/bin/bash
+
+# Note: Keep in sync with spark-*/run.sh (see README-accelerators.md for details)
+
+cat queries.sql | while read query; do
+    sync
+    echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null
+
+    ./query.py <<< "${query}"
+done