diff --git a/streaming/.ipynb_checkpoints/streaming-activities-checkpoint.ipynb b/streaming/.ipynb_checkpoints/streaming-activities-checkpoint.ipynb
new file mode 100644
index 0000000..c5235a0
--- /dev/null
+++ b/streaming/.ipynb_checkpoints/streaming-activities-checkpoint.ipynb
@@ -0,0 +1,343 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "            <div>\n",
+       "                <p><b>SparkSession - hive</b></p>\n",
+       "                \n",
+       "        <div>\n",
+       "            <p><b>SparkContext</b></p>\n",
+       "\n",
+       "            <p><a href=\"http://abhays-mbp-2:4040\">Spark UI</a></p>\n",
+       "\n",
+       "            <dl>\n",
+       "              <dt>Version</dt>\n",
+       "                <dd><code>v2.4.3</code></dd>\n",
+       "              <dt>Master</dt>\n",
+       "                <dd><code>local[*]</code></dd>\n",
+       "              <dt>AppName</dt>\n",
+       "                <dd><code>PySparkShell</code></dd>\n",
+       "            </dl>\n",
+       "        </div>\n",
+       "        \n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<pyspark.sql.session.SparkSession at 0x11d8e2f60>"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "spark"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "static = spark.read.json(\"../data/activity-data/\")\n",
+    "dataSchema = static.schema"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "root\n",
+      " |-- Arrival_Time: long (nullable = true)\n",
+      " |-- Creation_Time: long (nullable = true)\n",
+      " |-- Device: string (nullable = true)\n",
+      " |-- Index: long (nullable = true)\n",
+      " |-- Model: string (nullable = true)\n",
+      " |-- User: string (nullable = true)\n",
+      " |-- gt: string (nullable = true)\n",
+      " |-- x: double (nullable = true)\n",
+      " |-- y: double (nullable = true)\n",
+      " |-- z: double (nullable = true)\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "static.printSchema()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "+-------------+-------------------+--------+-----+------+----+-----+-------------+------------+------------+\n",
+      "| Arrival_Time|      Creation_Time|  Device|Index| Model|User|   gt|            x|           y|           z|\n",
+      "+-------------+-------------------+--------+-----+------+----+-----+-------------+------------+------------+\n",
+      "|1424686735090|1424686733090638193|nexus4_1|   18|nexus4|   g|stand|  3.356934E-4|-5.645752E-4|-0.018814087|\n",
+      "|1424686735292|1424688581345918092|nexus4_2|   66|nexus4|   g|stand| -0.005722046| 0.029083252| 0.005569458|\n",
+      "|1424686735500|1424686733498505625|nexus4_1|   99|nexus4|   g|stand|    0.0078125|-0.017654419| 0.010025024|\n",
+      "|1424686735691|1424688581745026978|nexus4_2|  145|nexus4|   g|stand| -3.814697E-4|   0.0184021|-0.013656616|\n",
+      "|1424686735890|1424688581945252808|nexus4_2|  185|nexus4|   g|stand| -3.814697E-4|-0.031799316| -0.00831604|\n",
+      "|1424686736094|1424686734097840342|nexus4_1|  218|nexus4|   g|stand| -7.324219E-4|-0.013381958|  0.01109314|\n",
+      "|1424686736294|1424688582347932252|nexus4_2|  265|nexus4|   g|stand| -0.005722046| 0.015197754| 0.022659302|\n",
+      "|1424686736495|1424688582549592408|nexus4_2|  305|nexus4|   g|stand| -3.814697E-4|0.0087890625|0.0034332275|\n",
+      "|1424686736697|1424688582750703248|nexus4_2|  345|nexus4|   g|stand|  0.002822876|-0.008300781|-0.015792847|\n",
+      "|1424686736898|1424688582952241334|nexus4_2|  385|nexus4|   g|stand|  6.866455E-4|-0.008300781| 0.004501343|\n",
+      "|1424686737100|1424686735109928643|nexus4_1|  418|nexus4|   g|stand|  0.003540039|-0.010177612|-0.026290894|\n",
+      "|1424686737300|1424688583355164918|nexus4_2|  465|nexus4|   g|stand|  0.002822876|0.0045166016|-0.014724731|\n",
+      "|1424686737505|1424686735512935017|nexus4_1|  498|nexus4|   g|stand| 0.0024719238|-0.010177612|-0.017745972|\n",
+      "|1424686737707|1424686735709254597|nexus4_1|  537|nexus4|   g|stand|-0.0028686523|-0.003768921| 0.020706177|\n",
+      "|1424686737908|1424686735915675495|nexus4_1|  578|nexus4|   g|stand|-0.0028686523| 0.026138306| 0.007888794|\n",
+      "|1424686738109|1424688584160372793|nexus4_2|  625|nexus4|   g|stand| -3.814697E-4| 2.441406E-4| 0.033340454|\n",
+      "|1424686738326|1424688584381747305|nexus4_2|  661|nexus4|   g|stand| 0.0017547607| 0.019470215|-0.011520386|\n",
+      "|1424686738529|1424686736534938191|nexus4_1|  701|nexus4|   g|stand| 0.0024719238|-0.033676147|0.0068206787|\n",
+      "|1424686738744|1424688584799723655|nexus4_2|  744|nexus4|   g|stand| -3.814697E-4|-0.002960205|-0.027542114|\n",
+      "|1424686738935|1424686736943477009|nexus4_1|  782|nexus4|   g|stand| -0.009277344|-0.009109497|  -0.0690155|\n",
+      "+-------------+-------------------+--------+-----+------+----+-----+-------------+------------+------------+\n",
+      "only showing top 20 rows\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "static.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Read one file at a time.. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "streaming = spark.readStream.schema(dataSchema)\\\n",
+    "  .option(\"maxFilesPerTrigger\", 1)\\\n",
+    "  .json(\"../data/activity-data\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Agrregation on streaming dataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "activityCounts = streaming.groupBy(\"gt\").count()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "####  Start stremaing query. Write output to memory.  OuputMode : `append`, `complete`, `update`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "activityQuery = activityCounts.writeStream.queryName(\"activity_counts\")\\\n",
+    "  .format(\"memory\")\\\n",
+    "  .outputMode(\"complete\")\\\n",
+    "  .start()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<pyspark.sql.streaming.StreamingQuery at 0x11d8ec6a0>]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "spark.streams.active"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Show output from in memory table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "+----------+------+\n",
+      "|        gt| count|\n",
+      "+----------+------+\n",
+      "|  stairsup|104570|\n",
+      "|       sit|123093|\n",
+      "|     stand|113850|\n",
+      "|      walk|132549|\n",
+      "|      bike|107962|\n",
+      "|stairsdown| 93637|\n",
+      "|      null|104463|\n",
+      "+----------+------+\n",
+      "\n",
+      "+----------+------+\n",
+      "|        gt| count|\n",
+      "+----------+------+\n",
+      "|  stairsup|104570|\n",
+      "|       sit|123093|\n",
+      "|     stand|113850|\n",
+      "|      walk|132549|\n",
+      "|      bike|107962|\n",
+      "|stairsdown| 93637|\n",
+      "|      null|104463|\n",
+      "+----------+------+\n",
+      "\n",
+      "+----------+------+\n",
+      "|        gt| count|\n",
+      "+----------+------+\n",
+      "|  stairsup|115029|\n",
+      "|       sit|135401|\n",
+      "|     stand|125235|\n",
+      "|      walk|145805|\n",
+      "|      bike|118759|\n",
+      "|stairsdown|102996|\n",
+      "|      null|114910|\n",
+      "+----------+------+\n",
+      "\n",
+      "+----------+------+\n",
+      "|        gt| count|\n",
+      "+----------+------+\n",
+      "|  stairsup|125490|\n",
+      "|       sit|147709|\n",
+      "|     stand|136619|\n",
+      "|      walk|159061|\n",
+      "|      bike|129556|\n",
+      "|stairsdown|112356|\n",
+      "|      null|125355|\n",
+      "+----------+------+\n",
+      "\n",
+      "+----------+------+\n",
+      "|        gt| count|\n",
+      "+----------+------+\n",
+      "|  stairsup|135951|\n",
+      "|       sit|160017|\n",
+      "|     stand|148003|\n",
+      "|      walk|172317|\n",
+      "|      bike|140353|\n",
+      "|stairsdown|121717|\n",
+      "|      null|135801|\n",
+      "+----------+------+\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from time import sleep\n",
+    "for x in range(5):\n",
+    "    spark.sql(\"SELECT * FROM activity_counts\").show()\n",
+    "    sleep(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "activityQuery.stop()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "spark.streams.active"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/streaming/.ipynb_checkpoints/streaming-wordcount-checkpoint.ipynb b/streaming/.ipynb_checkpoints/streaming-wordcount-checkpoint.ipynb
new file mode 100644
index 0000000..ec6461c
--- /dev/null
+++ b/streaming/.ipynb_checkpoints/streaming-wordcount-checkpoint.ipynb
@@ -0,0 +1,132 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pyspark.sql import SparkSession\n",
+    "from pyspark.sql.functions import explode\n",
+    "from pyspark.sql.functions import split"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "spark = SparkSession \\\n",
+    "    .builder \\\n",
+    "    .appName(\"StructuredNetworkWordCount\") \\\n",
+    "    .getOrCreate()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create DataFrame representing the stream of input lines from connection to localhost:9999\n",
+    "lines = spark \\\n",
+    "    .readStream \\\n",
+    "    .format(\"socket\") \\\n",
+    "    .option(\"host\", \"localhost\") \\\n",
+    "    .option(\"port\", 9999) \\\n",
+    "    .load()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Split the lines into words\n",
+    "words = lines.select(\n",
+    "   explode(\n",
+    "       split(lines.value, \" \")\n",
+    "   ).alias(\"word\")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate running word count\n",
+    "wordCounts = words.groupBy(\"word\").count()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Start running the query that prints the running counts to the console\n",
+    "query = wordCounts \\\n",
+    "    .writeStream \\\n",
+    "    .outputMode(\"complete\") \\\n",
+    "    .format(\"console\") \\\n",
+    "    .start()\n",
+    "\n",
+    "#query.awaitTermination()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#nc -lk 9999 "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Submit Job\n",
+    "#unset PYSPARK_DRIVER_PYTHON\n",
+    "#unset PYSPARK_DRIVER_PYTHON_OPTS\n",
+    "#\n",
+    "#$SPARK_HOME/bin/spark-submit $SPARK_HOME/examples/src/main/python/sql/streaming/structured_network_wordcount.py localhost 9999"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/streaming/streaming-activities.ipynb b/streaming/streaming-activities.ipynb
new file mode 100644
index 0000000..d154885
--- /dev/null
+++ b/streaming/streaming-activities.ipynb
@@ -0,0 +1,343 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "            <div>\n",
+       "                <p><b>SparkSession - hive</b></p>\n",
+       "                \n",
+       "        <div>\n",
+       "            <p><b>SparkContext</b></p>\n",
+       "\n",
+       "            <p><a href=\"http://abhays-mbp-2:4040\">Spark UI</a></p>\n",
+       "\n",
+       "            <dl>\n",
+       "              <dt>Version</dt>\n",
+       "                <dd><code>v2.4.3</code></dd>\n",
+       "              <dt>Master</dt>\n",
+       "                <dd><code>local[*]</code></dd>\n",
+       "              <dt>AppName</dt>\n",
+       "                <dd><code>PySparkShell</code></dd>\n",
+       "            </dl>\n",
+       "        </div>\n",
+       "        \n",
+       "            </div>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<pyspark.sql.session.SparkSession at 0x11d8e2f60>"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "spark"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "static = spark.read.json(\"../data/activity-data/\")\n",
+    "dataSchema = static.schema"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "root\n",
+      " |-- Arrival_Time: long (nullable = true)\n",
+      " |-- Creation_Time: long (nullable = true)\n",
+      " |-- Device: string (nullable = true)\n",
+      " |-- Index: long (nullable = true)\n",
+      " |-- Model: string (nullable = true)\n",
+      " |-- User: string (nullable = true)\n",
+      " |-- gt: string (nullable = true)\n",
+      " |-- x: double (nullable = true)\n",
+      " |-- y: double (nullable = true)\n",
+      " |-- z: double (nullable = true)\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "static.printSchema()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "+-------------+-------------------+--------+-----+------+----+-----+-------------+------------+------------+\n",
+      "| Arrival_Time|      Creation_Time|  Device|Index| Model|User|   gt|            x|           y|           z|\n",
+      "+-------------+-------------------+--------+-----+------+----+-----+-------------+------------+------------+\n",
+      "|1424686735090|1424686733090638193|nexus4_1|   18|nexus4|   g|stand|  3.356934E-4|-5.645752E-4|-0.018814087|\n",
+      "|1424686735292|1424688581345918092|nexus4_2|   66|nexus4|   g|stand| -0.005722046| 0.029083252| 0.005569458|\n",
+      "|1424686735500|1424686733498505625|nexus4_1|   99|nexus4|   g|stand|    0.0078125|-0.017654419| 0.010025024|\n",
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+      "|1424686735890|1424688581945252808|nexus4_2|  185|nexus4|   g|stand| -3.814697E-4|-0.031799316| -0.00831604|\n",
+      "|1424686736094|1424686734097840342|nexus4_1|  218|nexus4|   g|stand| -7.324219E-4|-0.013381958|  0.01109314|\n",
+      "|1424686736294|1424688582347932252|nexus4_2|  265|nexus4|   g|stand| -0.005722046| 0.015197754| 0.022659302|\n",
+      "|1424686736495|1424688582549592408|nexus4_2|  305|nexus4|   g|stand| -3.814697E-4|0.0087890625|0.0034332275|\n",
+      "|1424686736697|1424688582750703248|nexus4_2|  345|nexus4|   g|stand|  0.002822876|-0.008300781|-0.015792847|\n",
+      "|1424686736898|1424688582952241334|nexus4_2|  385|nexus4|   g|stand|  6.866455E-4|-0.008300781| 0.004501343|\n",
+      "|1424686737100|1424686735109928643|nexus4_1|  418|nexus4|   g|stand|  0.003540039|-0.010177612|-0.026290894|\n",
+      "|1424686737300|1424688583355164918|nexus4_2|  465|nexus4|   g|stand|  0.002822876|0.0045166016|-0.014724731|\n",
+      "|1424686737505|1424686735512935017|nexus4_1|  498|nexus4|   g|stand| 0.0024719238|-0.010177612|-0.017745972|\n",
+      "|1424686737707|1424686735709254597|nexus4_1|  537|nexus4|   g|stand|-0.0028686523|-0.003768921| 0.020706177|\n",
+      "|1424686737908|1424686735915675495|nexus4_1|  578|nexus4|   g|stand|-0.0028686523| 0.026138306| 0.007888794|\n",
+      "|1424686738109|1424688584160372793|nexus4_2|  625|nexus4|   g|stand| -3.814697E-4| 2.441406E-4| 0.033340454|\n",
+      "|1424686738326|1424688584381747305|nexus4_2|  661|nexus4|   g|stand| 0.0017547607| 0.019470215|-0.011520386|\n",
+      "|1424686738529|1424686736534938191|nexus4_1|  701|nexus4|   g|stand| 0.0024719238|-0.033676147|0.0068206787|\n",
+      "|1424686738744|1424688584799723655|nexus4_2|  744|nexus4|   g|stand| -3.814697E-4|-0.002960205|-0.027542114|\n",
+      "|1424686738935|1424686736943477009|nexus4_1|  782|nexus4|   g|stand| -0.009277344|-0.009109497|  -0.0690155|\n",
+      "+-------------+-------------------+--------+-----+------+----+-----+-------------+------------+------------+\n",
+      "only showing top 20 rows\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "static.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Read one file at a time.. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "streaming = spark.readStream.schema(dataSchema)\\\n",
+    "  .option(\"maxFilesPerTrigger\", 1)\\\n",
+    "  .json(\"../data/activity-data\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Agrregation on streaming dataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "activityCounts = streaming.groupBy(\"gt\").count()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "####  Start stremaing query. Write output to memory.  OuputMode : `append`, `complete`, `update`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "activityQuery = activityCounts.writeStream.queryName(\"activity_counts\")\\\n",
+    "  .format(\"memory\")\\\n",
+    "  .outputMode(\"complete\")\\\n",
+    "  .start()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<pyspark.sql.streaming.StreamingQuery at 0x11d930a58>]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "spark.streams.active"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Show output from in memory table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "+----------+-----+\n",
+      "|        gt|count|\n",
+      "+----------+-----+\n",
+      "|  stairsup|62741|\n",
+      "|       sit|73860|\n",
+      "|     stand|68311|\n",
+      "|      walk|79526|\n",
+      "|      bike|64775|\n",
+      "|stairsdown|56183|\n",
+      "|      null|62678|\n",
+      "+----------+-----+\n",
+      "\n",
+      "+----------+-----+\n",
+      "|        gt|count|\n",
+      "+----------+-----+\n",
+      "|  stairsup|73196|\n",
+      "|       sit|86169|\n",
+      "|     stand|79694|\n",
+      "|      walk|92781|\n",
+      "|      bike|75572|\n",
+      "|stairsdown|65546|\n",
+      "|      null|73127|\n",
+      "+----------+-----+\n",
+      "\n",
+      "+----------+------+\n",
+      "|        gt| count|\n",
+      "+----------+------+\n",
+      "|  stairsup| 83653|\n",
+      "|       sit| 98477|\n",
+      "|     stand| 91079|\n",
+      "|      walk|106036|\n",
+      "|      bike| 86367|\n",
+      "|stairsdown| 74914|\n",
+      "|      null| 83573|\n",
+      "+----------+------+\n",
+      "\n",
+      "+----------+------+\n",
+      "|        gt| count|\n",
+      "+----------+------+\n",
+      "|  stairsup| 94108|\n",
+      "|       sit|110785|\n",
+      "|     stand|102466|\n",
+      "|      walk|119292|\n",
+      "|      bike| 97164|\n",
+      "|stairsdown| 84277|\n",
+      "|      null| 94019|\n",
+      "+----------+------+\n",
+      "\n",
+      "+----------+------+\n",
+      "|        gt| count|\n",
+      "+----------+------+\n",
+      "|  stairsup|104570|\n",
+      "|       sit|123093|\n",
+      "|     stand|113850|\n",
+      "|      walk|132549|\n",
+      "|      bike|107962|\n",
+      "|stairsdown| 93637|\n",
+      "|      null|104463|\n",
+      "+----------+------+\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from time import sleep\n",
+    "for x in range(5):\n",
+    "    spark.sql(\"SELECT * FROM activity_counts\").show()\n",
+    "    sleep(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "activityQuery.stop()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "spark.streams.active"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/streaming/streaming-wordcount.ipynb b/streaming/streaming-wordcount.ipynb
new file mode 100644
index 0000000..ec6461c
--- /dev/null
+++ b/streaming/streaming-wordcount.ipynb
@@ -0,0 +1,132 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pyspark.sql import SparkSession\n",
+    "from pyspark.sql.functions import explode\n",
+    "from pyspark.sql.functions import split"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "spark = SparkSession \\\n",
+    "    .builder \\\n",
+    "    .appName(\"StructuredNetworkWordCount\") \\\n",
+    "    .getOrCreate()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create DataFrame representing the stream of input lines from connection to localhost:9999\n",
+    "lines = spark \\\n",
+    "    .readStream \\\n",
+    "    .format(\"socket\") \\\n",
+    "    .option(\"host\", \"localhost\") \\\n",
+    "    .option(\"port\", 9999) \\\n",
+    "    .load()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Split the lines into words\n",
+    "words = lines.select(\n",
+    "   explode(\n",
+    "       split(lines.value, \" \")\n",
+    "   ).alias(\"word\")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate running word count\n",
+    "wordCounts = words.groupBy(\"word\").count()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Start running the query that prints the running counts to the console\n",
+    "query = wordCounts \\\n",
+    "    .writeStream \\\n",
+    "    .outputMode(\"complete\") \\\n",
+    "    .format(\"console\") \\\n",
+    "    .start()\n",
+    "\n",
+    "#query.awaitTermination()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#nc -lk 9999 "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Submit Job\n",
+    "#unset PYSPARK_DRIVER_PYTHON\n",
+    "#unset PYSPARK_DRIVER_PYTHON_OPTS\n",
+    "#\n",
+    "#$SPARK_HOME/bin/spark-submit $SPARK_HOME/examples/src/main/python/sql/streaming/structured_network_wordcount.py localhost 9999"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}