tutorials/zh/6_interactive_query_with_gremlin.ipynb

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   "source": [
    "# 基于Gremlin的交互式查询\n",
    "Gremlin 是图数据领域最流行的查询语言之一，就好比关系型数据库里的 SQL 一样。接下来，我们将通过一些例子来说明 Gremlin 是如何执行图查询的。\n",
    "## 数据集\n",
    "MODERN，[tinkerpop](https://tinkerpop.apache.org/docs/current/tutorials/getting-started/)提供的示例数据集，由6个顶点和6条边组成。通过在 MODERN 基础上加入更多的边，方便我们展示更多的 gremlin 查询语句。这是图中包含的所有边：\n",
    "[(1,3),(1,2),(1,4),(4,5),(4,3),(6,3),(2,4),(4,1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import graphscope\n",
    "from graphscope.framework.graph import Graph\n",
    "from graphscope.framework.loader import Loader\n",
    "import vineyard\n",
    "\n",
    "k8s_volumes = {\n",
    "    \"data\": {\n",
    "        \"type\": \"hostPath\",\n",
    "        \"field\": {\n",
    "          \"path\": \"/testingdata/modern_graph_2\",  # Path in host\n",
    "          \"type\": \"Directory\"\n",
    "        },\n",
    "        \"mounts\": {\n",
    "          \"mountPath\": \"/home/jovyan/datasets/modern_graph_2\",  # Path in pods\n",
    "          \"readOnly\": True\n",
    "        }\n",
    "    }\n",
    "}\n",
    "graphscope.set_option(show_log=True)  # enable logging\n",
    "session = graphscope.session(k8s_volumes=k8s_volumes)  # create a session\n",
    "modern_graph = session.g()\n",
    "modern_graph = modern_graph.add_vertices(\n",
    "    Loader(\"/home/jovyan/datasets/modern_graph_2/person.csv\", delimiter=\"|\"),\n",
    "    label=\"person\"\n",
    ")\n",
    "modern_graph = modern_graph.add_vertices(\n",
    "    Loader(\"/home/jovyan/datasets/modern_graph_2/software.csv\", delimiter=\"|\"),\n",
    "    label=\"software\"\n",
    ")\n",
    "modern_graph = modern_graph.add_edges(\n",
    "    Loader(\"/home/jovyan/datasets/modern_graph_2/knows.csv\", delimiter=\"|\"),\n",
    "    label=\"knows\", src_label=\"person\", dst_label=\"person\"\n",
    ")\n",
    "modern_graph = modern_graph.add_edges(\n",
    "    Loader(\"/home/jovyan/datasets/modern_graph_2/created.csv\", delimiter=\"|\"),\n",
    "    label=\"created\", src_label=\"person\", dst_label=\"software\"\n",
    ")\n",
    "interactive = session.gremlin(modern_graph)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 两点之间的遍历\n",
    "两点之间的遍历是图数据领域十分常见的查询场景。例如，为了搞清楚v1和v2/v3之间的关系，我们可以这样写一条 gremlin 语句："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "q1 = interactive.execute(\"g.V().has(\\\"id\\\", 1).as(\\\"u\\\").out().has(\\\"id\\\", eq(2).or(eq(3))).as(\\\"v\\\").select(\\\"u\\\", \\\"v\\\").by(\\\"id\\\")\")\n",
    "for p in q1:\n",
    "    print(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "接下来展示一条在社交网络场景中常用的查询，例如如何找到两个不同用户之间的共同特点，用户1昵称为\"marko\"，另一个为\"peter\"。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "q2 = interactive.execute(\"g.V().has(\\\"name\\\", \\\"marko\\\").out().where(__.in().has(\\\"name\\\", \\\"peter\\\")).valueMap()\")\n",
    "for p in q2:\n",
    "    print(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 度的中心性\n",
    "度的中心性是衡量每个顶点邻接边数量的指标，在处理大数据时有重要意义，这里有一些示例："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "q3 = interactive.execute(\"g.V().group().by().by(bothE().count())\")\n",
    "for p in q3:\n",
    "    print(p[0])\n",
    "q4 = interactive.execute(\"g.V().group().by().by(inE().count())\")\n",
    "for p in q4:\n",
    "    print(p[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 环的检测\n",
    "环的检测是图查询在商业领域中的另一重要应用，环通常被认为是欺诈行为的发生。这里有一个示例展示 gremlin 如何被用于发现图上的环。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "q5 = interactive.execute(\"g.V().as(\\\"u\\\").repeat(out().simplePath()).times(2).where(out().where(eq(\\\"u\\\"))).count()\")\n",
    "print(q5.one())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 关闭会话，释放资源"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "session.close()"
   ]
  }
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