From 4dd04c5ae593a060ab5bfa4f440a14c8643cdbb8 Mon Sep 17 00:00:00 2001
From: Midgie MacFarland <160664522+midgemacf@users.noreply.github.com>
Date: Wed, 30 Sep 2026 09:35:21 -0400
Subject: [PATCH 1/5] Update Probe Data Storage Types  (#29)

`probe_data` table now has `value_float` and `value_jsonb` columns
instead of one `value` (jsonb type) column.

The migration will take the existing `value::jsonb` column and rename it
to `value_jsonb`. Then, will fill the `value_float` for any rows whose
`metric_type` is of `int` or `float` type.

On downgrade, undoes (casts `value_float` to jsonb in `value` col) so
that no data is lost.

Updated grafana dashboards accordingly, to pull from `value_float`
rather than `value` cast to `float`

---------

Co-authored-by: MacFarland, Midgie <macfarlandmj@ornl.gov>
---
 CHANGELOG.md                                  |  4 ++
 opensampl/db/orm.py                           |  3 +-
 opensampl/load_data.py                        | 28 +++++++---
 opensampl/metrics.py                          |  4 ++
 .../grafana/grafana-dashboards/ntp_dash.json  |  2 +-
 .../public-timing-dashboard.json              |  8 +--
 .../grafana-dashboards/public_twst_dash.json  | 12 ++--
 .../grafana-dashboards/timing-dashboard2.json |  8 +--
 .../grafana/grafana-dashboards/twst_dash.json | 12 ++--
 ...2026_09_11_1445_update_probe_data_types.py | 56 +++++++++++++++++++
 10 files changed, 106 insertions(+), 31 deletions(-)
 create mode 100644 opensampl/server/migrations/_migrations/versions/2026_09_11_1445_update_probe_data_types.py

diff --git a/CHANGELOG.md b/CHANGELOG.md
index bca537a..5e695e2 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -36,6 +36,10 @@ This project adheres to [Semantic Versioning](https://semver.org/).
 
 *Unreleased* versions radiate potential—-and dread. Once you merge an infernal PR, move its bullet under a new version heading with the actual release date.*
 
+### Changed
+- ⚡ `probe_data` table now has `value_float` and `value_jsonb` columns instead of one `value` (jsonb type) column. 
+- ⚡ …
+
 -->
 ## [1.2.1] - 2026-07-08
 ### Fixed
diff --git a/opensampl/db/orm.py b/opensampl/db/orm.py
index 2e104e6..7902559 100644
--- a/opensampl/db/orm.py
+++ b/opensampl/db/orm.py
@@ -280,7 +280,8 @@ class ProbeData(Base):
         primary_key=True,
         comment="Foreign key to the metric type being measured",
     )
-    value = Column(JSONB, comment="Measurement value stored as JSON; value's expected type defined via metric")
+    value_float = Column(Float, nullable=True, comment="Float type value; value's expected type defined via metric")
+    value_jsonb = Column(JSONB, nullable=True, comment="Measurement value stored as JSON; value's expected type defined via metric")
 
 
 class MetricType(Base):
diff --git a/opensampl/load_data.py b/opensampl/load_data.py
index d21f5ce..b4717bf 100644
--- a/opensampl/load_data.py
+++ b/opensampl/load_data.py
@@ -138,18 +138,28 @@ def load_time_data(
         df["probe_uuid"] = data_definition.probe.uuid  # ty: ignore[possibly-unbound-attribute]
         df["reference_uuid"] = data_definition.reference.uuid  # ty: ignore[possibly-unbound-attribute]
         df["metric_type_uuid"] = data_definition.metric.uuid  # ty: ignore[possibly-unbound-attribute]
-        logger.debug(df.head())
-        # Ensure correct dtypes
+
+        # Ensure correct time dtypes
         df["time"] = pd.to_datetime(df["time"], format="mixed", utc=True, errors="raise")
-        df["value"] = df["value"].apply(json.dumps)
+
+        if data_definition.metric.is_numeric():
+            df["value_float"] = pd.to_numeric(df["value"], errors="raise")
+            df["value_jsonb"] = None
+        else:
+            df["value_float"] = None
+            df["value_jsonb"] = df["value"].apply(json.dumps)
+
+        df = df.drop(columns=["value"])  # Drop original value column, as we now have value_float and value_jsonb
+        logger.debug(df.head())
+
         records = df.to_dict(orient="records")
         insert_stmt = text(f"""
-        INSERT INTO {ProbeData.__table__.schema}.{ProbeData.__tablename__}
-        (time, probe_uuid, reference_uuid, metric_type_uuid, value)
-        VALUES (:time, :probe_uuid, :reference_uuid, :metric_type_uuid, :value)
-        ON CONFLICT (time, probe_uuid, reference_uuid, metric_type_uuid)
-        DO NOTHING
-        """)  # noqa: S608
+                INSERT INTO {ProbeData.__table__.schema}.{ProbeData.__tablename__}
+                (time, probe_uuid, reference_uuid, metric_type_uuid, value_float, value_jsonb)
+                VALUES (:time, :probe_uuid, :reference_uuid, :metric_type_uuid, :value_float, :value_jsonb)
+                ON CONFLICT (time, probe_uuid, reference_uuid, metric_type_uuid)
+                DO NOTHING
+                """)  # noqa: S608
 
         try:
             result = session.execute(insert_stmt, records)
diff --git a/opensampl/metrics.py b/opensampl/metrics.py
index 27b6b8a..5fb28da 100644
--- a/opensampl/metrics.py
+++ b/opensampl/metrics.py
@@ -21,6 +21,10 @@ def convert_to_type(self, value: Any) -> Any:
         """Convert a given value to the expected type for the Metric"""
         return self.value_type(value)
 
+    def is_numeric(self) -> bool:
+        """Return True if the metric's value_type is numeric (int or float)"""
+        return self.value_type in [int, float]
+
     @field_serializer("value_type")
     def serialize_type(self, value: type):
         """Return the name of value_type for serializing"""
diff --git a/opensampl/server/grafana/grafana-dashboards/ntp_dash.json b/opensampl/server/grafana/grafana-dashboards/ntp_dash.json
index 345fd8c..6a8df53 100644
--- a/opensampl/server/grafana/grafana-dashboards/ntp_dash.json
+++ b/opensampl/server/grafana/grafana-dashboards/ntp_dash.json
@@ -1313,7 +1313,7 @@
               "editorMode": "code",
               "format": "table",
               "rawQuery": true,
-              "rawSql": "WITH probe_ref AS (\n    SELECT\n        uuid,\n        COALESCE(pm.name, CONCAT(pm.ip_address, ' ', pm.probe_id)) AS probe_name\n    FROM castdb.probe_metadata pm\n)\nSELECT\n    time_bucket('1 minute'::interval, pd.time AT TIME ZONE 'UTC') AS time,\n    pd.probe_uuid,\n    pr.probe_name,\n    pd.reference_uuid,\n    AVG(pd.value::float * 1e9) FILTER (WHERE lower(m.name) = 'phase offset') AS phase_offset,\n    AVG(pd.value::float * 1e9)  FILTER (WHERE lower(m.name) = 'jitter') AS jitter,\n    AVG((pd.value)::float) FILTER (WHERE lower(m.name) = 'stratum') AS stratum,\n    AVG((pd.value)::float) FILTER (WHERE lower(m.name) = 'sync health') AS sync_health\nFROM castdb.probe_data pd\nJOIN probe_ref pr\n    ON pd.probe_uuid = pr.uuid\nJOIN castdb.metric_type m\n    ON pd.metric_type_uuid = m.uuid\nWHERE pd.probe_uuid = ANY(ARRAY[${ntp_probe:sqlstring}]::text[]) AND $__timeFilter(pd.time)\nGROUP BY 1, 2, 3, 4\nORDER BY\n    1, 3;",
+              "rawSql": "WITH probe_ref AS (\n    SELECT\n        uuid,\n        COALESCE(pm.name, CONCAT(pm.ip_address, ' ', pm.probe_id)) AS probe_name\n    FROM castdb.probe_metadata pm\n)\nSELECT\n    time_bucket('1 minute'::interval, pd.time AT TIME ZONE 'UTC') AS time,\n    pd.probe_uuid,\n    pr.probe_name,\n    pd.reference_uuid,\n    AVG(pd.value_float * 1e9) FILTER (WHERE lower(m.name) = 'phase offset') AS phase_offset,\n    AVG(pd.value_float * 1e9)  FILTER (WHERE lower(m.name) = 'jitter') AS jitter,\n    AVG((pd.value)::float) FILTER (WHERE lower(m.name) = 'stratum') AS stratum,\n    AVG((pd.value)::float) FILTER (WHERE lower(m.name) = 'sync health') AS sync_health\nFROM castdb.probe_data pd\nJOIN probe_ref pr\n    ON pd.probe_uuid = pr.uuid\nJOIN castdb.metric_type m\n    ON pd.metric_type_uuid = m.uuid\nWHERE pd.probe_uuid = ANY(ARRAY[${ntp_probe:sqlstring}]::text[]) AND $__timeFilter(pd.time)\nGROUP BY 1, 2, 3, 4\nORDER BY\n    1, 3;",
               "refId": "A",
               "sql": {
                 "columns": [
diff --git a/opensampl/server/grafana/grafana-dashboards/public-timing-dashboard.json b/opensampl/server/grafana/grafana-dashboards/public-timing-dashboard.json
index 24b7a6f..68bd469 100644
--- a/opensampl/server/grafana/grafana-dashboards/public-timing-dashboard.json
+++ b/opensampl/server/grafana/grafana-dashboards/public-timing-dashboard.json
@@ -650,7 +650,7 @@
           "editorMode": "code",
           "format": "time_series",
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  coalesce(pm.name, concat(pm.ip_address, ' Interface ', pm.probe_id)),\n  AVG(pd.value::FLOAT) * 1e9 AS value\nFROM castdb.probe_data pd JOIN castdb.probe_metadata pm ON pd.probe_uuid = pm.uuid\nWHERE\n  $__timeFilter(pd.time)\n  AND pm.vendor IN ('ADVA', 'MicrochipTP4100', 'NTP')\n  AND coalesce(pm.public, true)\n  AND (trim('${clock_name:csv}') = '' OR pd.probe_uuid = ANY(string_to_array(trim('${clock_name:csv}'), ',')))\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid,\n  pm.name,\n  pm.ip_address,\n  pm.probe_id\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  coalesce(pm.name, concat(pm.ip_address, ' Interface ', pm.probe_id)),\n  AVG(pd.value_float) * 1e9 AS value\nFROM castdb.probe_data pd JOIN castdb.probe_metadata pm ON pd.probe_uuid = pm.uuid\nWHERE\n  $__timeFilter(pd.time)\n  AND pm.vendor IN ('ADVA', 'MicrochipTP4100', 'NTP')\n  AND coalesce(pm.public, true)\n  AND (trim('${clock_name:csv}') = '' OR pd.probe_uuid = ANY(string_to_array(trim('${clock_name:csv}'), ',')))\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid,\n  pm.name,\n  pm.ip_address,\n  pm.probe_id\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
           "refId": "A",
           "sql": {
             "columns": [
@@ -776,7 +776,7 @@
           "editorMode": "code",
           "format": "time_series",
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, CONCAT(pm.ip_address, ' Interface ', pm.probe_id)),\n  (MAX(pd.value::FLOAT) - MIN(pd.value::FLOAT)) * 1e9 AS value\nFROM castdb.probe_data pd JOIN castdb.probe_metadata pm ON pd.probe_uuid = pm.uuid\nWHERE\n  $__timeFilter(pd.time)\n  AND pm.vendor IN ('ADVA', 'MicrochipTP4100', 'NTP')\n  AND coalesce(pm.public, true)\n  AND (trim('${clock_name:csv}') = '' OR pd.probe_uuid = ANY(string_to_array(trim('${clock_name:csv}'), ',')))\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid,\n  pm.name,\n  pm.ip_address,\n  pm.probe_id\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, CONCAT(pm.ip_address, ' Interface ', pm.probe_id)),\n  (MAX(pd.value_float) - MIN(pd.value_float)) * 1e9 AS value\nFROM castdb.probe_data pd JOIN castdb.probe_metadata pm ON pd.probe_uuid = pm.uuid\nWHERE\n  $__timeFilter(pd.time)\n  AND pm.vendor IN ('ADVA', 'MicrochipTP4100', 'NTP')\n  AND coalesce(pm.public, true)\n  AND (trim('${clock_name:csv}') = '' OR pd.probe_uuid = ANY(string_to_array(trim('${clock_name:csv}'), ',')))\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid,\n  pm.name,\n  pm.ip_address,\n  pm.probe_id\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
           "refId": "A",
           "sql": {
             "columns": [
@@ -916,7 +916,7 @@
           "editorMode": "code",
           "format": "time_series",
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value::FLOAT) * 1e9 AS value\nFROM castdb.probe_data pd\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid = ${clock_name:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value_float) * 1e9 AS value\nFROM castdb.probe_data pd\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid = ${clock_name:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
           "refId": "A",
           "sql": {
             "columns": [
@@ -1027,7 +1027,7 @@
           "editorMode": "code",
           "format": "time_series",
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  (MAX(pd.value::FLOAT) - MIN(pd.value::FLOAT)) * 1e9 AS value\nFROM castdb.probe_data pd\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid = ${clock_name:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  (MAX(pd.value_float) - MIN(pd.value_float)) * 1e9 AS value\nFROM castdb.probe_data pd\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid = ${clock_name:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
           "refId": "A",
           "sql": {
             "columns": [
diff --git a/opensampl/server/grafana/grafana-dashboards/public_twst_dash.json b/opensampl/server/grafana/grafana-dashboards/public_twst_dash.json
index d3f4691..7858b93 100644
--- a/opensampl/server/grafana/grafana-dashboards/public_twst_dash.json
+++ b/opensampl/server/grafana/grafana-dashboards/public_twst_dash.json
@@ -493,7 +493,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  coalesce(pm.name, pm.probe_id) AS channel,\n  AVG(pd.value::FLOAT) AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${ebno_uuid:sqlstring}) pd\nJOIN \n  castdb.reference r ON pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nWHERE \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.name,\n  pm.probe_id\nORDER BY \n  time\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  coalesce(pm.name, pm.probe_id) AS channel,\n  AVG(pd.value_float) AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${ebno_uuid:sqlstring}) pd\nJOIN \n  castdb.reference r ON pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nWHERE \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.name,\n  pm.probe_id\nORDER BY \n  time\n",
           "refId": "B",
           "sql": {
             "columns": [
@@ -628,7 +628,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, pm.probe_id) as name,\n  AVG(pd.value::FLOAT) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nwhere \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, pm.probe_id) as name,\n  AVG(pd.value_float) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nwhere \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
@@ -763,7 +763,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, pm.probe_id) as name,\n  (MAX(pd.value::FLOAT) - MIN(pd.value::FLOAT)) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nwhere \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, pm.probe_id) as name,\n  (MAX(pd.value_float) - MIN(pd.value_float)) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nwhere \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
@@ -1246,7 +1246,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value::FLOAT) AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${ebno_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value_float) AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${ebno_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
@@ -1367,7 +1367,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value::FLOAT) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value_float) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
@@ -1488,7 +1488,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  (MAX(pd.value::FLOAT) - MIN(pd.value::FLOAT)) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  (MAX(pd.value_float) - MIN(pd.value_float)) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
diff --git a/opensampl/server/grafana/grafana-dashboards/timing-dashboard2.json b/opensampl/server/grafana/grafana-dashboards/timing-dashboard2.json
index bd23706..a108c40 100644
--- a/opensampl/server/grafana/grafana-dashboards/timing-dashboard2.json
+++ b/opensampl/server/grafana/grafana-dashboards/timing-dashboard2.json
@@ -653,7 +653,7 @@
           "editorMode": "code",
           "format": "time_series",
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  coalesce(pm.name, concat(pm.ip_address, ' Interface ', pm.probe_id)),\n  AVG(pd.value::FLOAT) * 1e9 AS value\nFROM castdb.probe_data pd join castdb.probe_metadata pm on pd.probe_uuid = pm.uuid\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid IN (${clock_name:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid,\n  pm.name,\n  pm.ip_address,\n  pm.probe_id\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  coalesce(pm.name, concat(pm.ip_address, ' Interface ', pm.probe_id)),\n  AVG(pd.value_float) * 1e9 AS value\nFROM castdb.probe_data pd join castdb.probe_metadata pm on pd.probe_uuid = pm.uuid\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid IN (${clock_name:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid,\n  pm.name,\n  pm.ip_address,\n  pm.probe_id\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
           "refId": "A",
           "sql": {
             "columns": [
@@ -778,7 +778,7 @@
           "editorMode": "code",
           "format": "time_series",
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(name, CONCAT(ip_address, ' Interface ', probe_id)),\n  (MAX(pd.value::FLOAT) - MIN(pd.value::FLOAT)) * 1e9 AS value\nFROM castdb.probe_data pd join castdb.probe_metadata pm on pd.probe_uuid = pm.uuid\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid in (${clock_name:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid,\n  pm.name,\n  pm.ip_address,\n  pm.probe_id\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(name, CONCAT(ip_address, ' Interface ', probe_id)),\n  (MAX(pd.value_float) - MIN(pd.value_float)) * 1e9 AS value\nFROM castdb.probe_data pd join castdb.probe_metadata pm on pd.probe_uuid = pm.uuid\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid in (${clock_name:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid,\n  pm.name,\n  pm.ip_address,\n  pm.probe_id\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
           "refId": "A",
           "sql": {
             "columns": [
@@ -917,7 +917,7 @@
           "editorMode": "code",
           "format": "time_series",
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value::FLOAT) * 1e9 AS value\nFROM castdb.probe_data pd\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid = ${clock_name:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value_float) * 1e9 AS value\nFROM castdb.probe_data pd\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid = ${clock_name:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
           "refId": "A",
           "sql": {
             "columns": [
@@ -1027,7 +1027,7 @@
           "editorMode": "code",
           "format": "time_series",
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  (MAX(pd.value::FLOAT) - MIN(pd.value::FLOAT)) * 1e9 AS value\nFROM castdb.probe_data pd\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid = ${clock_name:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  (MAX(pd.value_float) - MIN(pd.value_float)) * 1e9 AS value\nFROM castdb.probe_data pd\nWHERE\n  $__timeFilter(pd.time)\n  AND pd.probe_uuid = ${clock_name:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')\n",
           "refId": "A",
           "sql": {
             "columns": [
diff --git a/opensampl/server/grafana/grafana-dashboards/twst_dash.json b/opensampl/server/grafana/grafana-dashboards/twst_dash.json
index c90cad0..b4c59db 100644
--- a/opensampl/server/grafana/grafana-dashboards/twst_dash.json
+++ b/opensampl/server/grafana/grafana-dashboards/twst_dash.json
@@ -492,7 +492,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  coalesce(pm.name, pm.probe_id) AS channel,\n  AVG(pd.value::FLOAT) AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${ebno_uuid:sqlstring}) pd\nJOIN \n  castdb.reference r ON pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nWHERE \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.name,\n  pm.probe_id\nORDER BY \n  time\n",
+          "rawSql": "SELECT \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  coalesce(pm.name, pm.probe_id) AS channel,\n  AVG(pd.value_float) AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${ebno_uuid:sqlstring}) pd\nJOIN \n  castdb.reference r ON pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nWHERE \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.name,\n  pm.probe_id\nORDER BY \n  time\n",
           "refId": "B",
           "sql": {
             "columns": [
@@ -627,7 +627,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, pm.probe_id) as name,\n  AVG(pd.value::FLOAT) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nwhere \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, pm.probe_id) as name,\n  AVG(pd.value_float) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nwhere \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
@@ -762,7 +762,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, pm.probe_id) as name,\n  (MAX(pd.value::FLOAT) - MIN(pd.value::FLOAT)) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nwhere \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  COALESCE(pm.name, pm.probe_id) as name,\n  (MAX(pd.value_float) - MIN(pd.value_float)) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nJOIN \n  castdb.probe_metadata pm ON r.compound_reference_uuid = pm.uuid\nwhere \n  $__timeFilter(pd.time)\n  and r.compound_reference_uuid in (${compound_ref:sqlstring})\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pm.uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
@@ -1247,7 +1247,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value::FLOAT) AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${ebno_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value_float) AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${ebno_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
@@ -1368,7 +1368,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value::FLOAT) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  AVG(pd.value_float) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
@@ -1489,7 +1489,7 @@
           "format": "table",
           "hide": false,
           "rawQuery": true,
-          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  (MAX(pd.value::FLOAT) - MIN(pd.value::FLOAT)) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
+          "rawSql": "select \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC') AS time,\n  (MAX(pd.value_float) - MIN(pd.value_float)) * 1e9 AS value\nFROM \n  get_probe_data_by_probe_and_metric(${modem:sqlstring}, ${phase_offset_uuid:sqlstring}) pd\njoin castdb.reference r on pd.reference_uuid = r.uuid\nwhere \n  $__timeFilter(pd.time)\n  AND r.compound_reference_uuid = ${compound_ref:sqlstring}\nGROUP BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC'),\n  pd.probe_uuid\nORDER BY \n  time_bucket(${resolution:sqlstring}, pd.time AT TIME ZONE 'UTC')",
           "refId": "B",
           "sql": {
             "columns": [
diff --git a/opensampl/server/migrations/_migrations/versions/2026_09_11_1445_update_probe_data_types.py b/opensampl/server/migrations/_migrations/versions/2026_09_11_1445_update_probe_data_types.py
new file mode 100644
index 0000000..7c2688d
--- /dev/null
+++ b/opensampl/server/migrations/_migrations/versions/2026_09_11_1445_update_probe_data_types.py
@@ -0,0 +1,56 @@
+"""update probe_data types
+
+Revision ID: b88042bae240
+Revises: c95e49e551be
+Create Date: 2026-09-11 14:45:53.382353
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = 'b88042bae240'
+down_revision: Union[str, None] = 'c95e49e551be'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+SCHEMA = 'castdb'
+
+def upgrade() -> None:
+    op.alter_column("probe_data",
+                    "value",
+                    new_column_name="value_jsonb",
+                    nullable=True,
+                    schema=SCHEMA)
+    op.add_column("probe_data",
+                  sa.Column("value_float", sa.Float(), nullable=True),
+                  schema=SCHEMA)
+
+    # Backfill value_float from the numeric jsonb values
+    op.execute(
+        """
+        UPDATE castdb.probe_data pd
+        SET value_float = (pd.value_jsonb #>> '{}')::double precision
+        FROM castdb.metric_type mt
+        WHERE pd.metric_type_uuid = mt.uuid
+          AND mt.value_type IN ('float'
+            , 'int')
+        """
+    )
+
+
+def downgrade() -> None:
+    op.execute(
+        """
+        UPDATE castdb.probe_data
+        SET value_jsonb = to_jsonb(value_float)
+        WHERE value_float IS NOT NULL
+        """
+    )
+    op.drop_column("probe_data", "value_float", schema=SCHEMA)
+
+    op.alter_column("probe_data", "value_jsonb", nullable=False, new_column_name="value", schema=SCHEMA)

From bd4e24a218fbf667dfaddc2df03e7cf1dce9aad9 Mon Sep 17 00:00:00 2001
From: Joshua Grant <jngrant9@gmail.com>
Date: Wed, 30 Sep 2026 09:37:53 -0400
Subject: [PATCH 2/5] Update CHANGELOG for versions 1.2.1 and 1.2.2

Updated the CHANGELOG to include new version 1.2.2 and fixed CVEs in version 1.2.1.
---
 CHANGELOG.md | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5e695e2..227ceb8 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -36,11 +36,13 @@ This project adheres to [Semantic Versioning](https://semver.org/).
 
 *Unreleased* versions radiate potential—-and dread. Once you merge an infernal PR, move its bullet under a new version heading with the actual release date.*
 
+
+
+-->
+## [1.2.2] = 2026-09-30
 ### Changed
 - ⚡ `probe_data` table now has `value_float` and `value_jsonb` columns instead of one `value` (jsonb type) column. 
-- ⚡ …
 
--->
 ## [1.2.1] - 2026-07-08
 ### Fixed
 - 🩹 Addressed CVEs by updating minimum package versions for urllib3 2.7.0, pillow 12.3.0, mako 1.3.12, starlette 1.3.1, fastapi 0.139.0, idna 3.18, pytest 9.1.1, python-dotenv 1.2.2, fonttools 4.63.0, requests 2.34.2, markdown 3.10.2, pymdown-extensions 10.21.3, pygments 2.20.0, and python-multipart 0.0.32.

From 07d462ebf7cb6eded6f17d24723c355d8c78f3ad Mon Sep 17 00:00:00 2001
From: Joshua Grant <jngrant9@gmail.com>
Date: Wed, 30 Sep 2026 09:38:24 -0400
Subject: [PATCH 3/5] Bump version from 1.2.1 to 1.2.2

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 2b7be09..55369d2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "opensampl"
-version = "1.2.1"
+version = "1.2.2"
 description = "Python tools for adding clock data to a timescale db."
 license = {file = "LICENSE"}
 authors = [

From 85cc5206ef889007cd0fd39ae7e70e078f54fb7a Mon Sep 17 00:00:00 2001
From: Joshua Grant <jngrant9@gmail.com>
Date: Wed, 30 Sep 2026 09:41:34 -0400
Subject: [PATCH 4/5] Reformat columns for better readability in orm.py

---
 opensampl/db/orm.py | 26 +++++++++++++++++++++-----
 1 file changed, 21 insertions(+), 5 deletions(-)

diff --git a/opensampl/db/orm.py b/opensampl/db/orm.py
index 7902559..ea62e5c 100644
--- a/opensampl/db/orm.py
+++ b/opensampl/db/orm.py
@@ -280,8 +280,16 @@ class ProbeData(Base):
         primary_key=True,
         comment="Foreign key to the metric type being measured",
     )
-    value_float = Column(Float, nullable=True, comment="Float type value; value's expected type defined via metric")
-    value_jsonb = Column(JSONB, nullable=True, comment="Measurement value stored as JSON; value's expected type defined via metric")
+    value_float = Column(
+        Float, 
+        nullable=True, 
+        comment="Float type value; value's expected type defined via metric"
+    )
+    value_jsonb = Column(
+        JSONB, 
+        nullable=True, 
+        comment="Measurement value stored as JSON; value's expected type defined via metric"
+    )
 
 
 class MetricType(Base):
@@ -299,9 +307,17 @@ class MetricType(Base):
         default=lambda: str(uuid.uuid4()),
         comment="Auto generated primary key UUID for the metric type",
     )
-    name = Column(String, unique=True, comment="Unique name for the metric type (e.g., phase offset, delay, quality)")
-    description = Column(Text, nullable=True, comment="Optional human-readable description of the metric")
-    unit = Column(String, nullable=False, comment="Measurement unit (e.g., ns, s, ppm)")
+    name = Column(
+        String, 
+        unique=True, 
+        comment="Unique name for the metric type (e.g., phase offset, delay, quality)"
+    )
+    description = Column(
+        Text, nullable=True, comment="Optional human-readable description of the metric"
+    )
+    unit = Column(
+        String, nullable=False, comment="Measurement unit (e.g., ns, s, ppm)"
+    )
     value_type = Column(
         String, nullable=False, default="string", comment="Data type of the value (e.g., float, int, string)"
     )

From 41a22f06a08d32a779a8532015ed8fcf81b2a8ae Mon Sep 17 00:00:00 2001
From: "Grant, Josh" <grantjn@ornl.gov>
Date: Wed, 30 Sep 2026 10:27:20 -0400
Subject: [PATCH 5/5] lint: format opensample/db/orm.py with ruff

---
 opensampl/db/orm.py | 24 +++++-------------------
 1 file changed, 5 insertions(+), 19 deletions(-)

diff --git a/opensampl/db/orm.py b/opensampl/db/orm.py
index ea62e5c..5403ff3 100644
--- a/opensampl/db/orm.py
+++ b/opensampl/db/orm.py
@@ -280,15 +280,9 @@ class ProbeData(Base):
         primary_key=True,
         comment="Foreign key to the metric type being measured",
     )
-    value_float = Column(
-        Float, 
-        nullable=True, 
-        comment="Float type value; value's expected type defined via metric"
-    )
+    value_float = Column(Float, nullable=True, comment="Float type value; value's expected type defined via metric")
     value_jsonb = Column(
-        JSONB, 
-        nullable=True, 
-        comment="Measurement value stored as JSON; value's expected type defined via metric"
+        JSONB, nullable=True, comment="Measurement value stored as JSON; value's expected type defined via metric"
     )
 
 
@@ -307,17 +301,9 @@ class MetricType(Base):
         default=lambda: str(uuid.uuid4()),
         comment="Auto generated primary key UUID for the metric type",
     )
-    name = Column(
-        String, 
-        unique=True, 
-        comment="Unique name for the metric type (e.g., phase offset, delay, quality)"
-    )
-    description = Column(
-        Text, nullable=True, comment="Optional human-readable description of the metric"
-    )
-    unit = Column(
-        String, nullable=False, comment="Measurement unit (e.g., ns, s, ppm)"
-    )
+    name = Column(String, unique=True, comment="Unique name for the metric type (e.g., phase offset, delay, quality)")
+    description = Column(Text, nullable=True, comment="Optional human-readable description of the metric")
+    unit = Column(String, nullable=False, comment="Measurement unit (e.g., ns, s, ppm)")
     value_type = Column(
         String, nullable=False, default="string", comment="Data type of the value (e.g., float, int, string)"
     )