Project import generated by Copybara.

GitOrigin-RevId: d9e9e3fb4e31372ec1fb43b178994ca78fa8fe70
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Analyzing Rate Limit Exceeded events\n",
+    "\n",
+    "Use this notebook to dig into Rate Limit Exceeded events on Monorail."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import gcp\n",
+    "import gcp.bigquery as bq\n",
+    "\n",
+    "context = gcp.Context.default()\n",
+    "print 'The current project is %s' % context.project_id\n",
+    "\n",
+    "# Set the date to analyze here:\n",
+    "date = 20160514"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "%%sql --module by_ip\n",
+    "SELECT\n",
+    "  protoPayload.ip as ip,\n",
+    "  COUNT(protoPayload.requestId) AS num\n",
+    "FROM\n",
+    "  [logs.appengine_googleapis_com_request_log_$date]\n",
+    "WHERE\n",
+    "  protoPayload.moduleId is null # == \"default\", otherwise you get backend queries too.\n",
+    "  AND\n",
+    "  protoPayload.line.logMessage LIKE \"Rate Limit Exceeded%\"\n",
+    "GROUP BY\n",
+    "  ip\n",
+    "ORDER BY\n",
+    "  num DESC\n",
+    "LIMIT\n",
+    "  100;"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%%sql --module by_ip_class\n",
+    "SELECT\n",
+    "  REGEXP_EXTRACT(protoPayload.ip,r'^(?:[^\\.]*\\.){0}([^\\.]*)\\.?') AS a,\n",
+    "  REGEXP_EXTRACT(protoPayload.ip,r'^(?:[^\\.]*\\.){1}([^\\.]*)\\.?') AS b,\n",
+    "  REGEXP_EXTRACT(protoPayload.ip,r'^(?:[^\\.]*\\.){2}([^\\.]*)\\.?') AS c,\n",
+    "  REGEXP_EXTRACT(protoPayload.ip,r'^(?:[^\\.]*\\.){3}([^\\.]*)\\.?') AS d,\n",
+    "  COUNT(protoPayload.requestId) AS num\n",
+    "FROM\n",
+    "  [logs.appengine_googleapis_com_request_log_$date]\n",
+    "WHERE\n",
+    "  protoPayload.moduleId is null # == \"default\", otherwise you get backend queries too.\n",
+    "  AND\n",
+    "  protoPayload.line.logMessage LIKE \"Rate Limit Exceeded%\"\n",
+    "GROUP BY\n",
+    "  a,\n",
+    "  b,\n",
+    "  c,\n",
+    "  d\n",
+    "ORDER BY\n",
+    "  num DESC\n",
+    "LIMIT\n",
+    "  100;"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%%sql --module by_country\n",
+    "SELECT\n",
+    "  protoPayload.line.logMessage as line,\n",
+    "  COUNT(DISTINCT protoPayload.ip) as ip_count,\n",
+    "  COUNT(protoPayload.requestId) AS req_count\n",
+    "FROM\n",
+    "  FLATTEN ([logs.appengine_googleapis_com_request_log_$date], protoPayload.line)\n",
+    "WHERE\n",
+    "  protoPayload.moduleId is null # == \"default\", otherwise you get backend queries too.\n",
+    "  AND\n",
+    "  protoPayload.line.logMessage LIKE \"Rate Limit Exceeded%\"\n",
+    "  AND\n",
+    "  REGEXP_MATCH(protoPayload.line.logMessage, 'X-AppEngine-Country')\n",
+    "GROUP BY\n",
+    "  line\n",
+    "ORDER BY\n",
+    "  req_count DESC\n",
+    "LIMIT\n",
+    "  100;"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%%sql --module by_resource\n",
+    "SELECT\n",
+    "  protoPayload.resource as resource,\n",
+    "  COUNT(protoPayload.requestId) AS req_count\n",
+    "FROM\n",
+    "  [logs.appengine_googleapis_com_request_log_$date]\n",
+    "WHERE\n",
+    "  protoPayload.moduleId is null # == \"default\", otherwise you get backend queries too.\n",
+    "  AND\n",
+    "  protoPayload.line.logMessage LIKE \"Rate Limit Exceeded%\"\n",
+    "GROUP BY\n",
+    "  resource\n",
+    "ORDER BY\n",
+    "  req_count DESC\n",
+    "LIMIT\n",
+    "  100;"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Requests by IP"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "df = bq.Query(by_ip, date=date).to_dataframe()\n",
+    "df.head(20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "if len(df):\n",
+    "  df.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Requests by IP Class"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "df = bq.Query(by_ip_class,  date=date).to_dataframe()\n",
+    "df.head(20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "if len(df):\n",
+    "  df.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Requests by Country Code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "df = bq.Query(by_country, date=date).to_dataframe()\n",
+    "df.head(20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "if len(df):\n",
+    "  df.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Requests by Requested Resource"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "df = bq.Query(by_resource, date=date).to_dataframe()\n",
+    "df.head(20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "if len(df):\n",
+    "  df.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}