bi_4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# BI 4\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dg_builder import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- original\n",
    "\n",
    "> forum -> person -> city -> country\n",
    "\n",
    "- indexed\n",
    "\n",
    "> forum -> country\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Original\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File `./out/optimized/BI_4/data_graph.txt` & `./out/original/data_graph.txt` already exists\n"
     ]
    }
   ],
   "source": [
    "\"\"\" build `original data graph` \"\"\"\n",
    "\n",
    "build_original_dg(original_dg_filepath=BI_4_DG, optimized_dg_filepath=BI_4_DG_OPTIMIZED)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "QueryBuilder {\n",
       "    edges: [(0, 1), (1, 2), (2, 3)],\n",
       "    labels: ['forum', 'person', 'city', 'country'],\n",
       "    raw_task_names: [['bi_4_query_graph']],\n",
       "    QG_PRE: ./out/original/BI_4,\n",
       "    LOG_PRE: ./log/original/BI_4,\n",
       "    args_starting: ['wsl', './VEQ_M_100k', '-dg', './out/original/data_graph.txt', '-qg'],\n",
       "    replace_indices: [],\n",
       "    replace_wrapper: <function QueryBuilder.<lambda> at 0x000002138FA71120>,\n",
       "    kwargs: {'bi_4_query_graph': QGMetaRecord(labels=['forum', 'person', 'city', 'country'], edges=[(0, 1), (1, 2), (2, 3)])},\n",
       "}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\" labels & edges \"\"\"\n",
    "\n",
    "edges = [(0, 1), (1, 2), (2, 3)]\n",
    "labels = [\"forum\", \"person\", \"city\", \"country\"]\n",
    "task_names = [[\"bi_4_query_graph\"]]\n",
    "\n",
    "original_builder = QueryBuilder(\n",
    "    edges=edges,\n",
    "    labels=labels,\n",
    "    raw_task_names=task_names,\n",
    "    QG_PRE=BI_4_ORIGINAL_Q_PRE,\n",
    "    LOG_PRE=BI_4_ORIGINAL_L_PRE,\n",
    "    args_starting=bi_4_original_args_starting,\n",
    "    kwargs={},\n",
    ")\n",
    "\n",
    "original_builder.build()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>> Running: bi_4_query_graph...\n",
      "    Data file: ./out/original/data_graph.txt\n",
      "    Query file: ./out/original/BI_4/bi_4_query_graph.txt\n",
      "    Output file: \n",
      "    Sum of |C(u)|: 89019\n",
      "    Total Recursive Call Count: 160\n",
      "    Number of Matches: 100120\n",
      "    Filtering Time (ms): 124.918\n",
      "    Verification Time (ms): 245.836\n",
      "    Processing Time (ms): 370.754\n",
      "<<< Done! (Outer Elapsed Time: 22500.1903 ms)\n"
     ]
    }
   ],
   "source": [
    "\"\"\" exec \"\"\"\n",
    "\n",
    "time_table, outer_time_table = original_builder.run_with_elapsed_time_table_ret()\n",
    "assert len(time_table) == 1 and len(outer_time_table) == 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimized\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File `./out/optimized/BI_4/data_graph.txt` already exists\n"
     ]
    }
   ],
   "source": [
    "\"\"\" build `optimized data graph` \"\"\"\n",
    "\n",
    "index_csv_filenames = [\"forum_person_city_country\"]\n",
    "\n",
    "build_optimized_dg(\n",
    "    optimized_dg_filepath=BI_4_DG_OPTIMIZED,\n",
    "    index_csv_filenames=index_csv_filenames,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "QueryBuilder {\n",
       "    edges: [(0, 1)],\n",
       "    labels: ['forum', 'country'],\n",
       "    raw_task_names: [['bi_4_query_graph']],\n",
       "    QG_PRE: ./out/optimized/BI_4,\n",
       "    LOG_PRE: ./log/optimized/BI_4,\n",
       "    args_starting: ['wsl', './VEQ_M_100k', '-dg', './out/optimized/BI_4/data_graph.txt', '-qg'],\n",
       "    replace_indices: [],\n",
       "    replace_wrapper: <function QueryBuilder.<lambda> at 0x000002138FA71120>,\n",
       "    kwargs: {'bi_4_query_graph': QGMetaRecord(labels=['forum', 'country'], edges=[(0, 1)])},\n",
       "}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\" labels & edges \"\"\"\n",
    "\n",
    "edges_optimized: list[tuple[int, int]] = [(0, 1)]\n",
    "labels_optimized = [\"forum\", \"country\"]\n",
    "\n",
    "optimized_builder = QueryBuilder(\n",
    "    edges=edges_optimized,\n",
    "    labels=labels_optimized,\n",
    "    raw_task_names=task_names,\n",
    "    QG_PRE=BI_4_OPTIMIZED_Q_PRE,\n",
    "    LOG_PRE=BI_4_OPTIMIZED_L_PRE,\n",
    "    args_starting=bi_4_optimized_args_starting,\n",
    "    kwargs={},\n",
    ")\n",
    "\n",
    "optimized_builder.build()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>> Running: bi_4_query_graph...\n",
      "    Data file: ./out/optimized/BI_4/data_graph.txt\n",
      "    Query file: ./out/optimized/BI_4/bi_4_query_graph.txt\n",
      "    Output file: \n",
      "    Sum of |C(u)|: 53961\n",
      "<<< Done! (Outer Elapsed Time: 16335.4245 ms)\n",
      "--- Warning: No `Processing Time (ms)` detected in `task(bi_4_query_graph)` (`Outer Elapsed Time` is NOT accurate). ---\n",
      "--- ^^^^^^^^ `time_table` will be filled with `float(\"NaN\")` only for marking. ---\n"
     ]
    }
   ],
   "source": [
    "\"\"\" exec \"\"\"\n",
    "\n",
    "time_table_optimized, outer_time_table_optimized = (\n",
    "    optimized_builder.run_with_elapsed_time_table_ret()\n",
    ")\n",
    "assert len(time_table_optimized) == 1 and len(outer_time_table_optimized) == 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparison between: `original_match` & `optimized_match`\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (1, 5)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>task</th><th>original (ms)</th><th>optimized (ms)</th><th>original outer (ms)</th><th>optimized outer (ms)</th></tr><tr><td>list[str]</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td></tr></thead><tbody><tr><td>[&quot;bi_4_query_graph&quot;]</td><td>370.754</td><td>NaN</td><td>22500.1903</td><td>16335.4245</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (1, 5)\n",
       "┌──────────────────────┬───────────────┬────────────────┬─────────────────────┬─────────────────┐\n",
       "│ task                 ┆ original (ms) ┆ optimized (ms) ┆ original outer (ms) ┆ optimized outer │\n",
       "│ ---                  ┆ ---           ┆ ---            ┆ ---                 ┆ (ms)            │\n",
       "│ list[str]            ┆ f64           ┆ f64            ┆ f64                 ┆ ---             │\n",
       "│                      ┆               ┆                ┆                     ┆ f64             │\n",
       "╞══════════════════════╪═══════════════╪════════════════╪═════════════════════╪═════════════════╡\n",
       "│ [\"bi_4_query_graph\"] ┆ 370.754       ┆ NaN            ┆ 22500.1903          ┆ 16335.4245      │\n",
       "└──────────────────────┴───────────────┴────────────────┴─────────────────────┴─────────────────┘"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\" Show `comparison data-frame` \"\"\"\n",
    "\n",
    "print(\"Comparison between: `original_match` & `optimized_match`\")\n",
    "\n",
    "df = pl.DataFrame(\n",
    "    {\n",
    "        \"task\": task_names,\n",
    "        \"original (ms)\": time_table,\n",
    "        \"optimized (ms)\": time_table_optimized,\n",
    "        \"original outer (ms)\": outer_time_table,\n",
    "        \"optimized outer (ms)\": outer_time_table_optimized,\n",
    "    }\n",
    ")\n",
    "df"
   ]
  }
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