beef up the AI/ML framework tests by adding InfluxDB as data source and populate...

Change-Id: Ic8a72b7bf674d79d94007dc47f67cea3540136a1
Signed-off-by: pceicicd <pekwatch746@gmail.com>

diff --git a/XTesting/aiml-fw/cell.json b/XTesting/aiml-fw/cell.json
new file mode 100644 (file)
index 0000000..91ab1ba
--- /dev/null
+++ b/XTesting/aiml-fw/cell.json
@@ -0,0 +1,15401 @@
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+        },
+        "pdcpByteMeasReport": {
+          "pdcpBytesUl": 0.0,
+          "pdcpBytesDl": 0.0,
+          "measPeriodPdcpBytes": 10
+        }
+      },
+      {
+        "nrCellIdentity": "c8/N77",
+        "throughput": 0,
+        "x": -1664.0,
+        "y": 0.0,
+        "prbMeasReport": {
+          "availPrbDl": 273,
+          "availPrbUl": 273,
+          "measPeriodPrb": 10
+        },
+        "pdcpByteMeasReport": {
+          "pdcpBytesUl": 0.0,
+          "pdcpBytesDl": 0.0,
+          "measPeriodPdcpBytes": 10
+        }
+      }
+    ]
+  }
+}

diff --git a/XTesting/aiml-fw/deploy-aiml-thost.sh b/XTesting/aiml-fw/deploy-aiml-thost.sh
index edcf55c..717f4f7 100755 (executable)
--- a/XTesting/aiml-fw/deploy-aiml-thost.sh
+++ b/XTesting/aiml-fw/deploy-aiml-thost.sh
@@ -1,7 +1,7 @@
 #! /bin/bash
 set -x
 
-echo "This is to deploy the AI-ML framework training host"
+echo "This is to deploy the AI-ML framework training host and then add a notebook and sample data for a training test"
 
 if [ $# -lt 2 ]
 then 
@@ -15,6 +15,8 @@ KEYFILE=$2
 
 # copy over the deploy.sh to remote
 scp -o StrictHostKeyChecking=no -i $KEYFILE -q deploy.sh root@${IP}:~
+scp -o StrictHostKeyChecking=no -i $KEYFILE -q cell.json root@${IP}:~
+scp -o StrictHostKeyChecking=no -i $KEYFILE -q insert.py root@${IP}:~
 
 # copy remote IP to the hosts.yaml file
 echo "${IP}" >> hosts.yaml

diff --git a/XTesting/aiml-fw/deploy.sh b/XTesting/aiml-fw/deploy.sh
index 5ebd275..e472b90 100644 (file)
--- a/XTesting/aiml-fw/deploy.sh
+++ b/XTesting/aiml-fw/deploy.sh
@@ -7,3 +7,15 @@ git clone "https://gerrit.o-ran-sc.org/r/aiml-fw/aimlfw-dep" /aimlfw-dep
 cd /aimlfw-dep
 
 bin/install_traininghost.sh 2>&1 | tee /tmp/install-thost-`echo $RANDOM`.log
+
+# deploy InfluxDB as the data lake
+helm repo add bitnami https://charts.bitnami.com/bitnami
+helm install my-release bitnami/influxdb
+
+# install the dependencies for populating InfluxDB
+pip3 install pandas
+pip3 install influxdb-client
+
+# populate the sample data in InfluxDB as source for training
+cd /root
+python3 insert.py

diff --git a/XTesting/aiml-fw/insert.py b/XTesting/aiml-fw/insert.py
new file mode 100644 (file)
index 0000000..25983e4
--- /dev/null
+++ b/XTesting/aiml-fw/insert.py
@@ -0,0 +1,51 @@
+import pandas as pd
+from influxdb_client import InfluxDBClient
+from influxdb_client.client.write_api import SYNCHRONOUS
+import datetime
+
+
+class INSERTDATA:
+
+   def __init__(self):
+        self.client = InfluxDBClient(url = "http://localhost:8086", token="xJVlOom1GRUxDNkldo1v")
+
+
+def explode(df):
+     for col in df.columns:
+             if isinstance(df.iloc[0][col], list):
+                     df = df.explode(col)
+             d = df[col].apply(pd.Series)
+             df[d.columns] = d
+             df = df.drop(col, axis=1)
+     return df
+
+
+def jsonToTable(df):
+     df.index = range(len(df))
+     cols = [col for col in df.columns if isinstance(df.iloc[0][col], dict) or isinstance(df.iloc[0][col], list)]
+     if len(cols) == 0:
+             return df
+     for col in cols:
+             d = explode(pd.DataFrame(df[col], columns=[col]))
+             d = d.dropna(axis=1, how='all')
+             df = pd.concat([df, d], axis=1)
+             df = df.drop(col, axis=1).dropna()
+     return jsonToTable(df)
+
+
+def time(df):
+     df.index = pd.date_range(start=datetime.datetime.now(), freq='10ms', periods=len(df))
+     df['measTimeStampRf'] = df['measTimeStampRf'].apply(lambda x: str(x))
+     return df
+
+
+def populatedb():
+     df = pd.read_json('cell.json', lines=True)
+     df = df[['cellMeasReport']].dropna()
+     df = jsonToTable(df)
+     df = time(df)
+     db = INSERTDATA()
+     write_api = db.client.write_api(write_options=SYNCHRONOUS)
+     write_api.write(bucket="UEData",record=df, data_frame_measurement_name="liveCell",org="primary")
+
+populatedb()