Spark_Physics/HEP_benchmark/ADL_HEP_Query_Benchmark_Q6.ipynb

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  {
   "cell_type": "markdown",
   "id": "38491234",
   "metadata": {},
   "source": [
    "# HEP Benchmark Query Q6\n",
    "\n",
    "This follows the [IRIS-HEP benchmark](https://github.com/iris-hep/adl-benchmarks-index)\n",
    "and the article [Evaluating Query Languages and Systems for High-Energy Physics Data](https://arxiv.org/abs/2104.12615)\n",
    "and provides implementations of the benchmark tasks using Apache Spark.\n",
    "\n",
    "The workload and data:\n",
    "  - Benchmark jobs are implemented according to the [IRIS-HEP benchmark](https://github.com/iris-hep/adl-benchmarks-index)\n",
    "  - The input data is a series of events from CMS opendata\n",
    "  - The job output is typically a histogram \n",
    "  - See also https://github.com/LucaCanali/Miscellaneous/tree/master/Spark_Physics\n",
    "\n",
    "Author and contact: Luca.Canali@cern.ch  \n",
    "February, 2022\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e1ad2400",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Download the data if not yet available locally\n",
    "\n",
    "# Download the reduced data set (2 GB)\n",
    "! wget -r -np -R \"index.html*\" -e robots=off https://sparkdltrigger.web.cern.ch/sparkdltrigger/Run2012B_SingleMu_sample.parquet/\n",
    "\n",
    "# This downloads the full dataset (16 GB)\n",
    "# ! wget -r -np -R \"index.html*\" -e robots=off https://sparkdltrigger.web.cern.ch/sparkdltrigger/Run2012B_SingleMu.parquet/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "96c0e4a9-d443-4326-b3f1-03da4816d6a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install PySpark and sparkhistogram if needed\n",
    "# ! pip install pyspark\n",
    "! pip install sparkhistogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e218c19e-8db1-486d-aac2-14e0189e99dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Note: if you cannot install the package sparkhistogram, \n",
    "# create the computeHistogram function as detailed at the end of this notebook.\n",
    "# See https://github.com/LucaCanali/Miscellaneous/blob/master/Spark_Notes/Spark_DataFrame_Histograms.md \n",
    "\n",
    "from sparkhistogram import computeHistogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b5a25fca",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Start the Spark Session\n",
    "# This uses local mode for simplicity\n",
    "\n",
    "# The use of findspark is optional\n",
    "# import findspark\n",
    "# findspark.init(\"/home/luca/Spark/spark-3.5.1-bin-hadoop3\")\n",
    "\n",
    "from pyspark.sql import SparkSession\n",
    "spark = (SparkSession.builder\n",
    "         .appName(\"HEP benchmark\")\n",
    "         .master(\"local[4]\")\n",
    "         .config(\"spark.driver.memory\", \"8g\")\n",
    "         .config(\"spark.jars\", \"./scalaudf_2.12-0.1.jar\")  # jar with the Scala UDFs\n",
    "         .config(\"spark.jars.packages\", \"net.jafama:jafama:2.3.2\")  # Faster math library for Scala UDFs\n",
    "         .getOrCreate()\n",
    "        )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e00f87ee",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- run: integer (nullable = true)\n",
      " |-- luminosityBlock: long (nullable = true)\n",
      " |-- event: long (nullable = true)\n",
      " |-- HLT_IsoMu24_eta2p1: boolean (nullable = true)\n",
      " |-- HLT_IsoMu24: boolean (nullable = true)\n",
      " |-- HLT_IsoMu17_eta2p1_LooseIsoPFTau20: boolean (nullable = true)\n",
      " |-- PV_npvs: integer (nullable = true)\n",
      " |-- PV_x: float (nullable = true)\n",
      " |-- PV_y: float (nullable = true)\n",
      " |-- PV_z: float (nullable = true)\n",
      " |-- nMuon: long (nullable = true)\n",
      " |-- Muon_pt: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_eta: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_phi: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_mass: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_charge: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Muon_pfRelIso03_all: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_pfRelIso04_all: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_tightId: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Muon_softId: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Muon_dxy: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_dxyErr: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_dz: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_dzErr: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Muon_jetIdx: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Muon_genPartIdx: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- nElectron: long (nullable = true)\n",
      " |-- Electron_pt: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Electron_eta: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Electron_phi: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Electron_mass: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Electron_charge: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Electron_pfRelIso03_all: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Electron_dxy: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Electron_dxyErr: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Electron_dz: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Electron_dzErr: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Electron_cutBasedId: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Electron_pfId: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Electron_jetIdx: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Electron_genPartIdx: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- nTau: long (nullable = true)\n",
      " |-- Tau_pt: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Tau_eta: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Tau_phi: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Tau_mass: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Tau_charge: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Tau_decayMode: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Tau_relIso_all: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Tau_jetIdx: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Tau_genPartIdx: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Tau_idDecayMode: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idIsoRaw: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Tau_idIsoVLoose: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idIsoLoose: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idIsoMedium: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idIsoTight: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idAntiEleLoose: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idAntiEleMedium: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idAntiEleTight: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idAntiMuLoose: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idAntiMuMedium: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Tau_idAntiMuTight: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- nPhoton: long (nullable = true)\n",
      " |-- Photon_pt: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Photon_eta: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Photon_phi: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Photon_mass: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Photon_charge: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Photon_pfRelIso03_all: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Photon_jetIdx: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- Photon_genPartIdx: array (nullable = true)\n",
      " |    |-- element: integer (containsNull = true)\n",
      " |-- MET_pt: float (nullable = true)\n",
      " |-- MET_phi: float (nullable = true)\n",
      " |-- MET_sumet: float (nullable = true)\n",
      " |-- MET_significance: float (nullable = true)\n",
      " |-- MET_CovXX: float (nullable = true)\n",
      " |-- MET_CovXY: float (nullable = true)\n",
      " |-- MET_CovYY: float (nullable = true)\n",
      " |-- nJet: long (nullable = true)\n",
      " |-- Jet_pt: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Jet_eta: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Jet_phi: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Jet_mass: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      " |-- Jet_puId: array (nullable = true)\n",
      " |    |-- element: boolean (containsNull = true)\n",
      " |-- Jet_btag: array (nullable = true)\n",
      " |    |-- element: float (containsNull = true)\n",
      "\n",
      "Number of events: 6846198\n"
     ]
    }
   ],
   "source": [
    "# Read data for the benchmark tasks\n",
    "# download data as detailed at https://github.com/LucaCanali/Miscellaneous/tree/master/Spark_Physics\n",
    "\n",
    "path = \"sparkdltrigger.web.cern.ch/sparkdltrigger/\"\n",
    "input_data = \"Run2012B_SingleMu_sample.parquet\"\n",
    "\n",
    "# use this if you downloaded the full dataset\n",
    "# input_data = \"Run2012B_SingleMu.parquet\"\n",
    "\n",
    "df_events = spark.read.parquet(path + input_data)\n",
    "\n",
    "df_events.printSchema()\n",
    "\n",
    "print(f\"Number of events: {df_events.count()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8588faac",
   "metadata": {},
   "source": [
    "# Q6 - Solution 1: Offload all computations to Scala UDF\n",
    "For events with at least three jets, plot the $𝑝_𝑇$ of the trijet\n",
    "system four-momentum (i.e., any combination of three distinct jets within the same event) that has the invariant mass closest to 172.5 GeV in each event and plot the maximum\n",
    "b-tagging discriminant value among the jets in this trijet.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0b386dc9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- event: long (nullable = true)\n",
      " |-- Jet: array (nullable = true)\n",
      " |    |-- element: struct (containsNull = false)\n",
      " |    |    |-- Jet_pt: float (nullable = true)\n",
      " |    |    |-- Jet_eta: float (nullable = true)\n",
      " |    |    |-- Jet_phi: float (nullable = true)\n",
      " |    |    |-- Jet_mass: float (nullable = true)\n",
      " |    |    |-- Jet_btag: float (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Select 3-Jet events and group Jet parameters together\n",
    "\n",
    "df_events_q6 = ( df_events\n",
    "                 .selectExpr(\"event\", \"arrays_zip(Jet_pt, Jet_eta, Jet_phi, Jet_mass, Jet_btag) as Jet\")\n",
    "                 .filter(\"nJet >= 3\")\n",
    "               )\n",
    "                \n",
    "df_events_q6.printSchema()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4a58f9ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Register the Scala UDF\n",
    "schema = \"pt: float, btag: float\"\n",
    "\n",
    "spark.udf.registerJavaFunction(\"triJetSelectedPtBtag\", \"ch.cern.udf.triJetSelectedPtBtag\", schema)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "393a8972",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- trijet: struct (nullable = true)\n",
      " |    |-- pt: float (nullable = true)\n",
      " |    |-- btag: float (nullable = true)\n",
      "\n",
      "+-----------------------+\n",
      "|trijet                 |\n",
      "+-----------------------+\n",
      "|{21.191969, -1.0}      |\n",
      "|{11.904238, 0.92060655}|\n",
      "|{67.30781, 0.09140313} |\n",
      "|{50.762405, 0.19420531}|\n",
      "|{35.210625, 0.9639855} |\n",
      "+-----------------------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "q6 = df_events_q6.selectExpr(\"triJetSelectedPtBtag(Jet) as trijet\")\n",
    "\n",
    "q6.printSchema()\n",
    "q6.show(5, False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b02fc1a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute the histogram of trijet.btag\n",
    "# The Spark function \"width_bucket\" is used to generate the histogram bucket number\n",
    "# a groupBy operation with count is used to fill the histogram\n",
    "# The result is a histogram with bins value and counts foreach bin (N_events)\n",
    "\n",
    "min_val = 0\n",
    "max_val = 1.0\n",
    "num_bins = 100\n",
    "step = (max_val - min_val) / num_bins\n",
    "\n",
    "histogram_data = computeHistogram(q6, \"trijet.btag\", min_val, max_val, num_bins) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "243d3b64",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 328 ms, sys: 39.2 ms, total: 367 ms\n",
      "Wall time: 1min 57s\n"
     ]
    }
   ],
   "source": [
    "# The action toPandas() here triggers the computation.\n",
    "# Histogram data is fetched into the driver as a Pandas Dataframe.\n",
    "\n",
    "%time histogram_data_pandas=histogram_data.toPandas()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c9648762",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "plt.rcParams.update({'font.size': 20, 'figure.figsize': [14,10]})\n",
    "\n",
    "# cut the first and last bin\n",
    "x = histogram_data_pandas.iloc[1:-1][\"value\"]\n",
    "y = histogram_data_pandas.iloc[1:-1][\"count\"]\n",
    "\n",
    "# line plot\n",
    "f, ax = plt.subplots()\n",
    "ax.plot(x, y, '-')\n",
    "\n",
    "ax.set_xlabel('Jet b-tagging discriminant')\n",
    "ax.set_ylabel('Number of Events')\n",
    "ax.set_title(\"Distribution of Jet b-tagging discriminant\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f2e84581",
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute the histogram of trijet.pt\n",
    "\n",
    "min_val = 0\n",
    "max_val = 200\n",
    "num_bins = 100\n",
    "step = (max_val - min_val) / num_bins\n",
    "\n",
    "histogram_data = computeHistogram(q6, \"trijet.pt\", min_val, max_val, num_bins) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a853cd43",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 33.5 ms, sys: 6.96 ms, total: 40.5 ms\n",
      "Wall time: 1min 53s\n"
     ]
    }
   ],
   "source": [
    "# The action toPandas() here triggers the computation.\n",
    "# Histogram data is fetched into the driver as a Pandas Dataframe.\n",
    "\n",
    "%time histogram_data_pandas=histogram_data.toPandas()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "99099455",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "plt.rcParams.update({'font.size': 20, 'figure.figsize': [14,10]})\n",
    "\n",
    "# cut the first and last bin\n",
    "x = histogram_data_pandas.iloc[1:-1][\"value\"]\n",
    "y = histogram_data_pandas.iloc[1:-1][\"count\"]\n",
    "\n",
    "# line plot\n",
    "f, ax = plt.subplots()\n",
    "ax.plot(x, y, '-')\n",
    "\n",
    "ax.set_xlabel('$p_T$ (GeV)')\n",
    "ax.set_ylabel('Number of Events')\n",
    "ax.set_title(\"Distribution of $p_T$ \")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54984e19",
   "metadata": {},
   "source": [
    "# Q6 - Solution 2: Compute 3-jet combinations and TriJet mass in Scala UDF\n",
    "For events with at least three jets, plot the $𝑝_𝑇$ of the trijet\n",
    "system four-momentum (i.e., any combination of three distinct jets within the same event) that has the invariant mass closest to 172.5 GeV in each event and plot the maximum\n",
    "b-tagging discriminant value among the jets in this trijet.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "761bccdf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- event: long (nullable = true)\n",
      " |-- Jet: array (nullable = true)\n",
      " |    |-- element: struct (containsNull = false)\n",
      " |    |    |-- Jet_pt: float (nullable = true)\n",
      " |    |    |-- Jet_eta: float (nullable = true)\n",
      " |    |    |-- Jet_phi: float (nullable = true)\n",
      " |    |    |-- Jet_mass: float (nullable = true)\n",
      " |    |    |-- Jet_btag: float (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Select 3-Jet events and group Jet parameters together\n",
    "\n",
    "df_events_q6 = ( df_events\n",
    "                 .selectExpr(\"event\", \"arrays_zip(Jet_pt, Jet_eta, Jet_phi, Jet_mass, Jet_btag) as Jet\")\n",
    "                 .filter(\"nJet >= 3\")\n",
    "               )\n",
    "                \n",
    "df_events_q6.printSchema()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b1bf3340",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Register the Scala UDF\n",
    "\n",
    "# Alternative schema definition\n",
    "#from pyspark.sql.types import FloatType, ArrayType, StructType, StructField\n",
    "#\n",
    "#schema = ArrayType(ArrayType(StructType([\n",
    "#    StructField('pt', FloatType(), nullable=True),\n",
    "#    StructField('eta', FloatType(), nullable=True),\n",
    "#    StructField('phi', FloatType(), nullable=True),\n",
    "#    StructField('mass', FloatType(), nullable=True)\n",
    "#])))\n",
    "\n",
    "schema = \"array<array<struct<Jet_pt:float, Jet_eta:float, Jet_phi:float, Jet_mass:float, Jet_btag:float>>>\"\n",
    "\n",
    "spark.udf.registerJavaFunction(\"array_combinations\", \"ch.cern.udf.array_combinations\", schema)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a3b7c84a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- Jet_combinations: array (nullable = true)\n",
      " |    |-- element: array (containsNull = true)\n",
      " |    |    |-- element: struct (containsNull = true)\n",
      " |    |    |    |-- Jet_pt: float (nullable = true)\n",
      " |    |    |    |-- Jet_eta: float (nullable = true)\n",
      " |    |    |    |-- Jet_phi: float (nullable = true)\n",
      " |    |    |    |-- Jet_mass: float (nullable = true)\n",
      " |    |    |    |-- Jet_btag: float (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# use the Scala UDF to produce the trijet combinations\n",
    "df_jet_combinations = df_events_q6.selectExpr(\"array_combinations(Jet) as Jet_combinations\")\n",
    "\n",
    "df_jet_combinations.printSchema()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1997db3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Register the Scala UDF\n",
    "from pyspark.sql.types import StructType, StructField, FloatType\n",
    "\n",
    "schema = \"struct<mass:float, pt:float, btag:float>\"\n",
    "\n",
    "spark.udf.registerJavaFunction(\"compute_triJet_pt_mass_delta_btag\", \"ch.cern.udf.triJetPtMassDeltaBtag\", schema )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9a5d40c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- trijet: array (nullable = true)\n",
      " |    |-- element: struct (containsNull = true)\n",
      " |    |    |-- mass: float (nullable = true)\n",
      " |    |    |-- pt: float (nullable = true)\n",
      " |    |    |-- btag: float (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Compute the triJet btag using a Scala UDF\n",
    "\n",
    "df2 = df_jet_combinations.selectExpr(\"\"\"\n",
    "transform(Jet_combinations, trijet -> compute_triJet_pt_mass_delta_btag(trijet)) as trijet\n",
    "\"\"\")\n",
    "\n",
    "df2.printSchema()\n",
    "# df2.show(3, False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "dce53060",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- trijet: struct (nullable = true)\n",
      " |    |-- mass: float (nullable = true)\n",
      " |    |-- pt: float (nullable = true)\n",
      " |    |-- btag: float (nullable = true)\n",
      "\n",
      "+----------------------------------+\n",
      "|trijet                            |\n",
      "+----------------------------------+\n",
      "|{23.817657, 21.191969, -1.0}      |\n",
      "|{69.457016, 11.904238, 0.92060655}|\n",
      "|{203.42136, 67.30781, 0.09140313} |\n",
      "|{6.258835, 50.762405, 0.19420531} |\n",
      "|{12.777115, 35.210625, 0.9639855} |\n",
      "+----------------------------------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "3046954"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q6 = df2.selectExpr(\"array_min(trijet) as trijet\")\n",
    "\n",
    "q6.printSchema()\n",
    "q6.show(5, False)\n",
    "q6.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "103c9fc4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute the histogram\n",
    "\n",
    "min_val = 0\n",
    "max_val = 1\n",
    "num_bins = 100\n",
    "step = (max_val - min_val) / num_bins\n",
    "\n",
    "histogram_data = computeHistogram(q6, \"trijet.btag\", min_val, max_val, num_bins) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fadb7d95",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 57.8 ms, sys: 9.56 ms, total: 67.4 ms\n",
      "Wall time: 4min 37s\n"
     ]
    }
   ],
   "source": [
    "# The action toPandas() here triggers the computation.\n",
    "# Histogram data is fetched into the driver as a Pandas Dataframe.\n",
    "\n",
    "%time histogram_data_pandas=histogram_data.toPandas()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "99793cd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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dOtl17cKFC43Hc+fONQIPVj169NAdd9yh//u//9OyZct08OBBxcXF6U9/+pPCwsIUFhams2fPGueHhYVV2+xfsvx1uHPnzpo/f36dgwELFizQ3XffrenTp5d7vnv37urbt6/uvvtuFRYWasWKFfrzn/+sDh061Gm8c0VGRioyMtL4h7r1uZq+BucqKSnR1KlTjSDYgw8+qClTppQ7p0uXLrr11ls1ceJEfffdd0pLS9PLL7+sN998s8r7vv7667r22mv13//+t1xZa5cuXdSrVy/deOONKiws1K5du7R3795az1uS/vGPfxi/uPfs2VNz5swpl83RuXNnDRo0SJdffrlmzpypkpISPffcc1qzZo38/Pzk6+trjBsWFmZc16JFC4fm4yxPP/20EQSbNm2aUYZmdcUVV2j48OGaPHmyvvvuO+3fv19vv/22nnjiCUlyeH3Y49ixY0pOTtasWbMqZNdde+21uvTSS/XSSy9JspTkDh8+vNZrzfb7Ut1zkuX1axtwmjVrVoXASZ8+fXTzzTdr8ODBysvL05dffqnx48erefPm5c579913jcBM+/bttWjRIiO4KEm9e/fWwIED9ec//7lcUO5c+fn5euONN4yPJ0yYoMcee8z4+LLLLtNNN92kZ555RosXLy43hqMOHDignTt3Vlq2dfXVVys4ONgImH/11VcVAmGLFi0ysg+jo6O1ePFiow+kZHk/vummmzRy5Mhq17295syZY7w+r7jiCs2fP7/c+0T37t01dOhQ3XvvvVq2bJlDY6SnpxvXRkdH6+OPP1ZoaGi5c3r37q177rlH99xzjw4ePKilS5dq8uTJ5TIs//WvfxlBsJEjR5bL5pIsgbFevXpp3LhxMpvNmjFjhgYNGlTpbsorV65USEiIPvnkkwpzqa233npLTz75pMaNG2c816lTJ1111VUaOHCgcnJyFB8fr+3bt2v06NFGUNx6Xu/evfXHP/5Rx48fV3Jysn7//fcKP4ftVZf3e2euYWfMqU2bNpJUbl22bt3aKWX8ADzb+dFBFgBQZ15eXrr44ouNj0+cOGH3tdYm3hEREVX+49vb21tPPPGEHn30Uf39738v1yPIEWfPntXkyZOdsmtf48aNNXXq1EqPXXbZZbr55puNj1esWFHn8erL+vXrje9Fq1atqsz28Pb21gsvvGD8QhEXF6dTp05Ve+9XX3210t1EW7Zsqauvvtr42JFdL9PT042/4nt5eenll1+utKRJksaMGWMEaK3le+4qPj5ev/76qySpf//+FYJgVr6+vnrxxReNX9YWLVpUrvynvpjNZv3hD3+ossT03nvvNX5hTElJ0aZNm+p1PhkZGRo0aJBuuOEG/eEPf6gye6hFixZG6VdJSYnRZ8nKbDZr+fLlxsf/93//V2mA6tprr9UDDzygnJycKucUHx9vlBg3b95cf/7znyucYzKZ9MILL+iiiy6q9l72ysvL0w033FBl76Lhw4cbj/fu3VvhtfL1118bjx977LFyQTCrDh06aMqUKXWer9lsLhfceuqppyp9n4iIiKgQdKqNw4cPq6ioSJLUrVu3KgNPEREReu655zR58mS98sor8vb2No5lZGQYWc9hYWFGsPlc1mCYZMl2++677yo97+zZs3rkkUfqHASTLH27HnzwwQrPN27cuNz7q7+/v5588skK5/n7+5frfbVnz546zcfR93tnrWFnzgkAKkMgDABgsG1AnpKSYvd1/v7+kizlbef2QbIVGxuriRMnavjw4cZfah0VFhZW7h+/dTFo0KBqy1n+8Ic/GI+3bNnilDHrg7UcUJJuueWWSnsHWUVFRal3796SpOLi4kr77lhdd911ioyMrPJ427Ztjce1ed1YbdiwweitdNVVV6lly5ZVnmsymTR48GDj43Xr1tV6vIZiG6SrqSFz48aNjQbf6enpRsP1+nbrrbdWeczLy6tcr6H6fu1HRETo+eef1+zZs43SqqpYS30lVQji7t27V2fOnJFkeZ+wvs4rM2rUqGrXycaNG43HAwcOrPJcf39/3XfffdXOuTZsg13natKkiRF8KSwsNDIOJUsfLWsgwGQyVboBg9XQoUPVqFGjOs3z4MGDxh9NGjVqpO7du1d5bu/evcuVwdaGbQBkz5491fZ16927tx5++GENGTKk3Oe3YcMG5eXlSbIEQavL3ps6dareffddff7551X22zKZTHUq9bR14403Vtmvzfa1ft111xk/b6s7zzaDtLbq8n7vrDXszDkBQGUIhAEADLZZONZfGOxh/et5cXGxRo4cqcWLFzvcr8tebdq0cVqj5yuuuKLa47bN5A8ePOiUMeuDbWllVTuH2bItfd21a1eV53Xu3Lna+9huIFCb141VbedtO5/q5u1qCQkJxmN7NoewbfK8e/fu+phSBTV9vW2zRF3x2jebzUpLS9OBAweMRuZ79+4tF/w5t0H9oUOHjMft27cvlxV0rsjIyGpLwG3vZe1LVJWadiqsjZoaftuuudzcXOPxoUOHjD5lzZo1U+PGjau8h5+fn/He7ShrBqpk6dtVXV8qk8nkcCPzdu3aGZltiYmJGjVqlNatW6fi4mK772G7CUdNGckdOnRQ//791aVLlyqDhZGRkRV2r3VUdaXOtgG76jY2sT2vLps2OPv93pE1XN9zAgB6hAEADOnp6cbj2vwD/+mnn1ZCQoJOnz6tkydP6plnntH06dN1xRVXqGfPnurdu7e6dOlSbeZFbVX3C15t1dQvxDaLIS0tTcXFxdX+cu0qx48fNx7b0wMlNjbWeHzy5Mkqz6vptWAbkHSkWfixY8eMx/bM27aXTHXzdjXbLIfqMq8qU5vSZEf5+vqqWbNm1Z5j+9q3zbTIycmpsCPhufd2NOvz5MmTmj9/vtauXasjR47UukzU9utuTzPsDh06VNhBsLJ71fS1atu2rXx9fZ1S1uromnPkc1+5cmXtJ1jKdv3Zk+1l+55TG76+vnrppZc0fvx4FRYWatu2bXrooYcUERGhnj176uqrr1bv3r3Vrl27Ku9h+3q1NkuvC2f+DAoPD6/ymO33uroyzLq+D1s54/2+rmu4PuYEALYIhAEADNZyIkm1KpmJjY3VF198oX/9619atmyZCgsLlZ+fr40bN2rjxo1688031bhxYw0ePFgPPvigU3Zqsm2IXle2f02uzLn9qnJzc2u8xhVs/8JuT9Nu23LQ7OzsKs+r76CfbfZgbedd35mHdWEbWK6thvi8goKCatxZzvZrbZt59Ntvv2nUqFFVXhcbG6vvv/++1nNas2aNnnrqqTr1rrKdpz2vp+reS2znUdNugCaTSWFhYU4pzXJ0zTnzc7dHbb4+9s6pKtddd50++ugj/fOf/zT61aWlpWn16tVavXq1JEum8PDhw3XfffdVmI/te5wzdpB15s8ge7ObG+IPMHUdwxlr+Fzu+IcnAJ6NQBgAQJLlF++9e/caH9e2mX1MTIxmzpypSZMmadWqVVq3bp22bNlilDykpqZqwYIF+vzzzzVjxowqG3Tby1llkfbc69y/MDu6LX19q+28SkpKHL7WlWy/H858HTib7dzmz59fq+BydRkizmLP99z2a13fr5F9+/Zp8uTJxntGp06ddP/996tbt26KiIhQaGioMYfZs2frrbfeqvQ+tX1dV/dLdm1fa65+PTrzc6+P8WpTyliZbt26af78+dq1a5e+++47rVu3Tjt37jTmcejQIf3jH//Qxx9/rP/+97/lfo7Zzs923o5y9ffaHTlrDQNAfSMQBgCQJP3888/GLynt27evdKcxe8TExGj06NEaPXq08vPztXXrVv3444/66quvdPbsWeXl5enJJ59U69atq+3N05Bq+su1bc8Rk8nkcFZDXX8JrEloaKiRjZKVlVVj+Y/t5+2Mnc8cZTu2PZlQtpkdrpz3uc4NBISGhhq/EDZp0qRcQ2d3YE/Ghm2GUXBwsPH46quvrvPOdOeaN2+e8fXq0aOH3n///Up3iZOqX0u22T729AuqLnPPNhvU9mtRFdusTFdw5udeH+NVl3laGx07dlTHjh01YcIEpaWlKT4+XnFxcVq9erUKCgqUnJysP//5z1qxYoXxfm2bxevOmaSezFlrGADqG3/KAABIkt5//33j8Q033OCUe/r7++uaa67RtGnTtGbNGmN795KSEr399ttOGcMZbHtUVca2X1NUVFS5gEdtsgzqspOXPWz77xw9erTG82175tTU/6g+2c77yJEjNZ7fUPM+depUjfOx7X1zbrmV7e6X1e2m6ioFBQXlyqErY9sDyhl9lapjLXeTpEcffbTKX6AlVdufzLaf0OnTp2scd9++fU6515EjR1zeqNuZn7s9oqKijMc1vZYk+9Z3bUVEROjGG2/U66+/rhUrVhgbUxw/flxLliwxzrNdjzW958MxzlrDAFDfCIQBAPTNN98YO9yFhoZW2/vHUcHBwXruueeMj23LMF3Ndjexythmvtjuoiep3Fb2NWU7VNWQ21m6dOliPN62bVuN52/fvt14fPnll9fLnOxhO+9ff/21xvNtv471Me+4uDj17NlTffv21QsvvFDleYWFheWCm+dmUdrOLT4+3unzdIbavPara0TuDLaBm+rGysvL0/r166s8ftFFFxmPawr0pKenl9u19FytWrUyHu/fv7/ae23YsKHa4w3B9nNPTk6uNoutuLhYGzdurNN4tu+HNX2ti4uLq/1aO0PLli316KOPGh/b/pyx3XnQ9r2vMtu3b9drr72m1157TWvWrHH+RM9TzlrDAFDfCIQBwAVu27Zt5QJU48ePr1UT4B9++EHTpk3T7bffXuNOd7ZlbNU1Ky4qKrJ7fGdYuXKlCgoKqjweFxdnPO7du3e5Y7Z9nw4cOFDlPfLy8rR8+XK75+TI12DQoEHG46+//rraz+no0aP65ZdfJFkaWPft27fW4znLtddea5QvJSQk6ODBg1WeW1RUpG+++cb42FnZi7Yuvvhio2Rs8+bN5Xbis5WQkGBkhF188cUV1s2f/vQn4/FXX31VY9ncpEmTNGrUKH3wwQfVfu+cuT6++uqrKo8VFhbqhx9+MD4+97XvqKrmb1uGmJaWVuX17777brnj596vU6dOxr1OnTql//3vf1Xea8GCBUYpV2W6detmPF67dm2V5xUUFGjBggVVHm8o0dHRRoZlYWFhtcG5b775psrXtr0uvvhiIwvt5MmT1Qa61q5dW+33tTrz58/XxIkT9cADD9S4K2BVP2f69u1rvC62bNlSbVbYwoULNWfOHM2ZM0epqakOzflC5Kw1XJ8oyQQgEQgDgAtWYWGhPvroI40ePdroFXTzzTdr9OjRtbrPqVOntGTJEu3cuVMvvfRStb/AL1y40Hhs+wumVH4HroYuIztx4oTeeOONSo9t3brV2JHMx8enQpP/Dh06GE2TDx06pK1bt1a4h9ls1vTp05WRkVHtPOr6NejVq5eR9ZCcnKxZs2ZVel5+fr7+8pe/GKWcw4cPd+kumCEhIbrrrrskWb5Wzz77bJUlZm+++aYSExMlWfoEOSs4Y6t169a6+uqrJVnWyfPPP1/hl6eCggL961//Mj4eNmxYhft0795dV1xxhSTLL4VTp06tcn18/PHHWrlypTZt2qTVq1dXKCmqj/VhMpn07bff6scff6z0+Pvvv2+URrZs2bLCmq0ta4AiNTW10h5NHTp0MB6vXLmy0ntYm6DbBm6Tk5PLnRMQEKB+/foZH7/22muV/vK7adMmvfPOO9UG/q+77jrje7Fnzx59+eWXFc4xm836+9//rqNHj9ZpV0RnsQ0Ov/nmm5X2gtu3b59mzJhR550PfXx89Mc//tH4+NVXX600qJGSkqJXXnnF4Q0Xtm/frm+//VYbNmzQnDlzqjyvqKhIn332mfGx7Ws2JCREd955pyRLMOSvf/1rudJmq4SEBK1YscK4xjagjeo5aw07m21w1PrzA8CFjWb5AHAeKigoqLT0MCcnR2fOnNEvv/yi1atXl/vH51133aVnn3221mMNHTpUH3zwgQ4cOKC4uDjddtttGjp0qDp27KhGjRopPz9fJ06c0OrVq41/GAcFBWns2LHl7tOiRQt5eXmppKREO3bs0IsvvqguXbooJSVFw4YNK9f7xtnGjh2ruXPnav/+/Ro6dKhatmyp/Px8bdy4UXPnzjV+ib777rvL9ZmRLBlh/fv3N7JFHnvsMT366KPq0qWLfH19dfDgQS1cuNDIvHvxxRernIftvePi4vTPf/5Tbdu21YkTJ/Twww/b9bnMmDFDd955p/Ly8vTee+9p//79GjZsmPE57dq1Sx9//LFR5tWuXTtNnjy5Vl+v+jBhwgT9+OOPOnjwoLZu3aphw4Zp9OjR6tChg0wmkw4fPqwvv/zSKKcJCgrSq6++Wm/zeeaZZzR8+HAVFhbq+++/18iRI3XvvfeqVatWOnbsmN577z2jjPPSSy/VvffeW+l9ZsyYoTvuuEOZmZmKi4vT8OHDNWLECF166aUqLi5WUlKSvvrqK/3000+SLKW2f/nLXyrcpz7Wx8UXX6zmzZvrscce0x133KHrrrtOUVFROnv2rFauXKkvvvjCOPepp56q866RF110kXbu3KnCwkJNnDhRN910k/Ly8tS1a1dddtllGjp0qLZs2SJJmjNnjgoKCvSHP/xB/v7+OnjwoJYsWaItW7bo+uuv1/3332+8FtasWaPly5froosuUvv27eXn56dHH31Ua9asUXFxsX766SeNGDFCI0aMUKtWrZSVlaW4uDgtWrRIzZs316BBgzR37txK59y4cWONGDFC7733niTpL3/5i37//XcNGDBA4eHhOnz4sD766CNt3bpVjzzyiL7++mu7NiGoT2PHjtWnn36qnJwc7d27V3feeafGjh2rSy65RPn5+Vq/fr3mz58vPz8/jRs3Tq+99lqdxnvkkUf0zTffKCcnR5s2bdK9996r0aNHq1WrVsrLy9P27dv1/vvvKz09XXfffbc++eSTWo/x2GOPac2aNcrNzdXrr7+u+Ph43XTTTWrZsqXCwsKUlZWlgwcPaunSpca67Nixo66//vpy95kwYYLWrVunxMREbdiwQXfffbdGjRqltm3bKj09XfHx8Vq4cKERIJs6dapbbcjh7py5hp3JtmT45ZdfVnJysnx9fRUeHl4vWcUA3B+BMAA4Dx0+fFhDhgyx69w2bdpo4sSJuvHGGx0ay8/PT3PnztWjjz6qXbt2af/+/dX+YhUTE6NZs2ZVCCiFhoZq8ODBRtnbwoULjQyyP/7xj/UaCHvggQd0+vRpff311+VKwWz169dPTz/9dKXHnn32Wf3vf//TyZMndfbsWf3973+vcM748eM1dOjQagNh7du315VXXmmU3L3zzjvGMXsDYe3bt9f8+fM1fvx4nTx5UuvWrdO6desqPbdnz55644033CKLJSgoSAsWLND48eOVkJCg/fv3669//Wul58bGxurNN9/UpZdeWm/z6dChg/7zn//oqaeeUnp6urZu3Vpptl/nzp31n//8p1xJkK02bdpo4cKFGj9+vA4fPqw9e/ZU+Xk1bdpUr732WrleRlb1sT5MJpNefvllPfTQQ/r444/18ccfV3rO+PHjnZIVc8899xjB9g0bNhhlezNmzNBll12mYcOGae3atYqLi1NxcbHee+89IwBlNWjQIL3++uvy9vZWixYtlJSUpJycHD3xxBOSpB9//FExMTHq2LGjXnzxRT3//PMqKipSQkKC0QfRqlWrVnrvvfe0dOnSauc9efJk7du3T+vXr1dRUZEWLFhQoQzyzjvv1IQJE/T111/X6WvkDE2bNtUbb7yhCRMmKDc3V/v27dO0adPKndO4cWPNmzdPu3fvrvN4zZo10xtvvKGJEycqJydH27dvN74fVn5+fvrb3/7m8G6Nbdu21X//+1898cQTSk1N1c8//6yff/65yvOvuOIKzZ49W76+vuWeDw0N1Ycffqjx48drx44d+v333/V///d/Fa739fXVlClTdMcddzg03wuVM9ewM91xxx2aP3++iouLlZiYqOnTp0uSbrvtNgJhwAWKQBgAXEB8fHzUqFEjNWnSRN27d1efPn3Ur18/o7TPUc2bN9cXX3yhVatWafXq1dq1a5dOnz6tvLw8+fv7q3Hjxrr00ks1YMAADRkypMr+YC+88IKCg4P1ww8/KCUlReHh4WrXrp2Cg4PrNL+a+Pv76x//+IcGDBigpUuXavfu3UpNTVVwcLA6dOig2267TbfeemuVGTEtWrTQ0qVL9d5772ndunVKSkpSfn6+GjVqpB49emjkyJHq0aNHjc30JWn27Nl6+eWXtWnTJmVkZKhRo0a1Dvh07dpVq1ev1uLFi7V27Vrt2bNHZ8+ela+vr5o0aaJu3bpp8ODB6t+/f63uW9+ioqL0ySefKC4uTitXrtSvv/6qlJQUlZSUqFGjRurYsaMGDBigoUOHOj1joDL9+vXTt99+q48//lg//vijDh06pNzcXIWHh6tjx44aPHiwbr31Vnl7e1d7n/bt22v58uX65ptvtGbNGu3cuVNnz55VSUmJIiIi1KFDB1133XUaOnRotUFJZ68PX19f42u+aNEirVy5UkeOHFFmZqYaNWqk7t27a8SIEerRo4dD9z/X8OHDlZ2drUWLFikpKUlBQUFq2bKlERQ3mUx688039dlnn+nLL7/U/v37lZeXp/DwcHXp0kX33HOP+vXrZ6zD//73v3rppZe0c+dOeXt7q2PHjuW+fsOHD1fnzp31wQcfaMuWLTp9+rR8fHzUpk0bDR06VHfccYcCAwPL9Zyq7L3Qz89Pc+bM0eLFi/X1119r7969yszMVFhYmK644gqNGjVKvXr1kqRy96rpdVGf+vXrp2+++Ubz5s3Tzz//rJMnT8psNuuiiy7STTfdpPvuu0/h4eHatWuXcU1dfg7069dPy5cv13vvvaf169fr5MmTMplMatq0qa6++mrdd999at++faWlpfbq3bu3Vq1apSVLlmj9+vU6cOCAUlNTVVhYqMDAQMXExKhz58668cYbdd1111X5fh0TE6NPP/1Uy5cv18qVK7Vr1y6lpKTI29tbzZs31zXXXKORI0eWyyKCfZy9hp2lXbt2mjNnjmbNmqX9+/fLy8tL0dHRuuyyy5w+FgDPYDLX1HESAAAAOE/NmDFDH3zwgSRLdufIkSMdvlfPnj2NjRa2bt3q0t579pg/f76RwXr//fdr6tSpLp4RAAD1j2b5AAAAuGAdOnTIeNysWTOH75OSkmIEwcLCwtw+CCaV/9ydXY4GAIC7ojQSAAAA55XVq1drw4YNOnTokO65554Ku71aZWRkaPPmzZIsZV3n7oxZUFCgd999VwcPHtSxY8c0b968KktR16xZYzyu6w6bdREfH6+4uDgdOnRI/fr105gxYyo9r7i42NjkQ5KuvPLKBpohAACuRSAMAAAA55WkpCR9+umnkqRTp06pV69eaty4cblzzGazXn75ZeXm5kqS+vfvr6ioqHLn+Pn5adWqVcYuvLNnz660fPDkyZN68803jY+HDRvm1M+nNjIyMvTRRx9Jknbt2qUBAwZU2u/qrbfe0vHjxyVJl1xyibp06dKg8wQAwFXoEQYAAIDzSnZ2tm699VYdPXpUkmWn0VGjRqlTp04KCgrS4cOHtWjRIiMbLDAwUF988YUuvvjiCvf64Ycf9PDDDxuN8Pv27avbb79dLVq0UGFhoRISEvTBBx/ozJkzkqRevXrp/fffr/MmJI4qKSnRPffco19//VWSZYfIESNG6Morr1RYWJiOHTumr776St99950kS5P89957T71793bJfAEAaGgEwgAAAHDeOXz4sB5++GEdPHiw2vMaNWqkWbNmVRsI+vzzz/Xiiy+qoKCg2ntdc801mjVrliIiIhyZstOkpKToscce07Zt26o9LzAwUH//+981ePDgBpoZAACuRyAMAAAA56XCwkJ9/fXXWr16tXbv3q3U1FS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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "plt.rcParams.update({'font.size': 20, 'figure.figsize': [14,10]})\n",
    "\n",
    "# cut the first and last bin\n",
    "x = histogram_data_pandas.iloc[1:-1][\"value\"]\n",
    "y = histogram_data_pandas.iloc[1:-1][\"count\"]\n",
    "\n",
    "# line plot\n",
    "f, ax = plt.subplots()\n",
    "ax.plot(x, y, '-')\n",
    "\n",
    "ax.set_xlabel('Jet b-tagging discriminant')\n",
    "ax.set_ylabel('Number of Events')\n",
    "ax.set_title(\"Distribution of Jet b-tagging discriminant\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ec10ccf5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute the histogram\n",
    "\n",
    "min_val = 0\n",
    "max_val = 200\n",
    "num_bins = 100\n",
    "step = (max_val - min_val) / num_bins\n",
    "\n",
    "histogram_data = computeHistogram(q6, \"trijet.pt\", min_val, max_val, num_bins) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b4beb275",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 43:====================================================>   (15 + 1) / 16]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 51.5 ms, sys: 15 ms, total: 66.4 ms\n",
      "Wall time: 4min 35s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# The action toPandas() here triggers the computation.\n",
    "# Histogram data is fetched into the driver as a Pandas Dataframe.\n",
    "\n",
    "%time histogram_data_pandas=histogram_data.toPandas()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "55bc6d91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "plt.rcParams.update({'font.size': 20, 'figure.figsize': [14,10]})\n",
    "\n",
    "# cut the first and last bin\n",
    "x = histogram_data_pandas.iloc[1:-1][\"value\"]\n",
    "y = histogram_data_pandas.iloc[1:-1][\"count\"]\n",
    "\n",
    "# line plot\n",
    "f, ax = plt.subplots()\n",
    "ax.plot(x, y, '-')\n",
    "\n",
    "ax.set_xlabel('$p_T$ (GeV)')\n",
    "ax.set_ylabel('Number of Events')\n",
    "ax.set_title(\"Distribution of $p_T$ \")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2598a2d",
   "metadata": {},
   "source": [
    "# Q6 - Solution 3: Only TriJet mass in Scala UDF\n",
    "For events with at least three jets, plot the $𝑝_𝑇$ of the trijet\n",
    "system four-momentum (i.e., any combination of three distinct jets within the same event) that has the invariant mass closest to 172.5 GeV in each event and plot the maximum\n",
    "b-tagging discriminant value among the jets in this trijet.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "fc8d5edf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- event: long (nullable = true)\n",
      " |-- Jet: array (nullable = true)\n",
      " |    |-- element: struct (containsNull = false)\n",
      " |    |    |-- Jet_pt: float (nullable = true)\n",
      " |    |    |-- Jet_eta: float (nullable = true)\n",
      " |    |    |-- Jet_phi: float (nullable = true)\n",
      " |    |    |-- Jet_mass: float (nullable = true)\n",
      " |    |    |-- Jet_btag: float (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Select 3-Jet events and group Jet parameters together\n",
    "\n",
    "df_events_q6 = ( df_events\n",
    "                 .selectExpr(\"event\", \n",
    "                             \"arrays_zip(Jet_pt, Jet_eta, Jet_phi, Jet_mass, Jet_btag) as Jet\")\n",
    "                 .filter(\"nJet >= 3\")\n",
    "               )\n",
    "                \n",
    "df_events_q6.printSchema()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "9f9b109c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+---+----------------------------------------------------+\n",
      "|pos|Jet                                                 |\n",
      "+---+----------------------------------------------------+\n",
      "|0  |{28.03698, -2.573142, -0.0039507723, 9.169433, -1.0}|\n",
      "|1  |{20.425129, -0.6191127, 2.44285, 6.7956524, -1.0}   |\n",
      "|2  |{18.646175, 2.5256636, 1.2553711, 5.9932246, -1.0}  |\n",
      "|3  |{17.995762, -3.8685246, 1.146259, 5.420945, -10.0}  |\n",
      "|4  |{17.04349, -3.4595842, 2.2116172, 5.1888537, -10.0} |\n",
      "+---+----------------------------------------------------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df_events_q6.selectExpr(\"posexplode(Jet) as (pos, Jet)\").show(5, False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2cd0ec94",
   "metadata": {},
   "outputs": [],
   "source": [
    "schema = \"struct<mass:float, pt:float, btag: float>\"\n",
    "\n",
    "spark.udf.registerJavaFunction(\"compute_triJet_pt_mass_btag\", \"ch.cern.udf.triJetPtMassBtag\", schema )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "4ada4349",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "24/05/07 16:12:04 WARN SparkStringUtils: Truncated the string representation of a plan since it was too large. This behavior can be adjusted by setting 'spark.sql.debug.maxToStringFields'.\n"
     ]
    }
   ],
   "source": [
    "df_events_q6.createOrReplaceTempView(\"t1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "81bbcd7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# explodes Jet data for all possible 3-jet combinations\n",
    "# compute pt and mass with a UDF \n",
    "# filter for the desired combination\n",
    "\n",
    "df_3jets = spark.sql(\"\"\"\n",
    "with triJet_all as (\n",
    "  select e1 as event, compute_triJet_pt_mass_btag(j1.Jet, j2.Jet, j3.Jet) as triJet_pt_mass_btag\n",
    "  from\n",
    "    (select event e1, posexplode(Jet) as (pos, Jet) from t1) j1,\n",
    "    (select event e2, posexplode(Jet) as (pos, Jet) from t1) j2,\n",
    "    (select event e3, posexplode(Jet) as (pos, Jet) from t1) j3\n",
    "  where\n",
    "    j1.pos < j2.pos and j2.pos < j3.pos\n",
    "    and e1 = e2 and e1 = e3\n",
    ")\n",
    "select event, triJet_pt_mass_btag, \n",
    "       rank() over (partition by event order by abs(triJet_pt_mass_btag.mass - 172.5)) triJet_rank\n",
    "from triJet_all\n",
    "\"\"\")\n",
    "\n",
    "\n",
    "#df_3jets.show(10, False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7dd7ebee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- event: long (nullable = true)\n",
      " |-- triJet_pt_mass_btag: struct (nullable = true)\n",
      " |    |-- mass: float (nullable = true)\n",
      " |    |-- pt: float (nullable = true)\n",
      " |    |-- btag: float (nullable = true)\n",
      " |-- triJet_rank: integer (nullable = false)\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 56:>                                                         (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-----+----------------------------------+-----------+\n",
      "|event|triJet_pt_mass_btag               |triJet_rank|\n",
      "+-----+----------------------------------+-----------+\n",
      "|47430|{169.13412, 56.775955, 0.04395841}|1          |\n",
      "|50104|{183.86757, 38.0367, -1.0}        |1          |\n",
      "|63012|{231.37935, 19.84785, 0.939022}   |1          |\n",
      "|70734|{172.78848, 31.175726, 0.93264025}|1          |\n",
      "|84492|{65.63297, 30.16877, -10.0}       |1          |\n",
      "+-----+----------------------------------+-----------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "df_3jets_selected = df_3jets.filter(\"triJet_rank == 1\")\n",
    "\n",
    "df_3jets_selected.printSchema()\n",
    "df_3jets_selected.show(5, False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "359b0ea1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute the histogram\n",
    "\n",
    "min_val = 0\n",
    "max_val = 1\n",
    "num_bins = 100\n",
    "step = (max_val - min_val) / num_bins\n",
    "\n",
    "histogram_data = computeHistogram(df_3jets_selected, \"triJet_pt_mass_btag.btag\", min_val, max_val, num_bins) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "bb8a5cd2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 60:======================================================> (33 + 1) / 34]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 53.2 ms, sys: 9.59 ms, total: 62.8 ms\n",
      "Wall time: 1min 58s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "%time histogram_data_pandas=histogram_data.toPandas()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "749391fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "plt.rcParams.update({'font.size': 20, 'figure.figsize': [14,10]})\n",
    "\n",
    "# cut the first and last bin\n",
    "x = histogram_data_pandas.iloc[1:-1][\"value\"]\n",
    "y = histogram_data_pandas.iloc[1:-1][\"count\"]\n",
    "\n",
    "# line plot\n",
    "f, ax = plt.subplots()\n",
    "ax.plot(x, y, '-')\n",
    "\n",
    "ax.set_xlabel('Jet b-tagging discriminant')\n",
    "ax.set_ylabel('Number of Events')\n",
    "ax.set_title(\"Distribution of Jet b-tagging discriminant\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1c699b94",
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute the histogram\n",
    "\n",
    "min_val = 0\n",
    "max_val = 200\n",
    "num_bins = 100\n",
    "step = (max_val - min_val) / num_bins\n",
    "\n",
    "histogram_data = computeHistogram(df_3jets_selected, \"triJet_pt_mass_btag.pt\", min_val, max_val, num_bins) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "2c45cdf9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 74:======================================================> (33 + 1) / 34]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 45.2 ms, sys: 17.6 ms, total: 62.7 ms\n",
      "Wall time: 1min 58s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "%time histogram_data_pandas=histogram_data.toPandas()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "2e4111f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "plt.rcParams.update({'font.size': 20, 'figure.figsize': [14,10]})\n",
    "\n",
    "# cut the first and last bin\n",
    "x = histogram_data_pandas.iloc[1:-1][\"value\"]\n",
    "y = histogram_data_pandas.iloc[1:-1][\"count\"]\n",
    "\n",
    "# line plot\n",
    "f, ax = plt.subplots()\n",
    "ax.plot(x, y, '-')\n",
    "\n",
    "ax.set_xlabel('$p_T$ (GeV)')\n",
    "ax.set_ylabel('Number of Events')\n",
    "ax.set_title(\"Distribution of $p_T$ \")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4f9a51d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "spark.stop()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b3dfc97-7d67-4a5b-8b34-0fc06819b540",
   "metadata": {},
   "source": [
    "## Note on sparkhistogram\n",
    "\n",
    "Use this to define the computeHistogram function if you cannot ! pip install sparkhistogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ccfdbed6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def computeHistogram(df: \"DataFrame\", value_col: str, min_val: float, max_val: float, bins: int) -> \"DataFrame\":\n",
    "    \"\"\" This is a dataframe function to compute the count/frequecy histogram of a column\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        df: the dataframe with the data to compute\n",
    "        value_col: column name on which to compute the histogram\n",
    "        min: minimum value in the histogram\n",
    "        max: maximum value in the histogram\n",
    "        bins: number of histogram buckets to compute\n",
    "        \n",
    "        Output DataFrame\n",
    "        ----------------\n",
    "        bucket: the bucket number, range from 1 to bins (included)\n",
    "        value: midpoint value of the given bucket\n",
    "        count: number of values in the bucket        \n",
    "    \"\"\"\n",
    "    # Compute the step size for the histogram\n",
    "    step = (max_val - min_val) / bins\n",
    "\n",
    "    # Get the Spark Session handle\n",
    "    spark = SparkSession.getActiveSession()\n",
    "\n",
    "    # df_buckets is the range of {bins} buckets as requested by the user\n",
    "    # It will be used to fill in for missing buckets, i.e. buckets with no corresponding values\n",
    "    df_buckets = spark.range(bins).selectExpr(\"id + 1 as bucket\")\n",
    "\n",
    "    # Group user data into buckets and count their population count\n",
    "    df_grouped = (df\n",
    "                   .selectExpr(f\"width_bucket({value_col}, {min_val}, {max_val}, {bins}) as bucket\")\n",
    "                   .groupBy(\"bucket\")\n",
    "                   .count()\n",
    "                 )\n",
    "\n",
    "    # join df_buckets with the grouped data to fill in missing buckets\n",
    "    df_hist = (df_buckets # note this will be typically broadcasted, the order of the join is important\n",
    "               .join(df_grouped, \"bucket\", \"left_outer\") # add missing buckets and remove buckets out of range\n",
    "               .selectExpr(\"bucket\", f\"{min_val} + (bucket - 0.5) * {step} as value\",  # use center value of the buckets\n",
    "                           \"nvl(count, 0) as count\") # buckets with no values will have a count of 0\n",
    "               .orderBy(\"bucket\")\n",
    "              )\n",
    "\n",
    "    return df_hist\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1c88bea1-e9e3-4971-8e56-4f36f0fd8e47",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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