Data Lake measurements endpoint returns no data series when no data between startDate and endDate

[bossenti]

Apache StreamPipes version

dev (current development state)

Affected StreamPipes components

Backend

What happened?

The endpoint for data lake measurements allows to filter the data records when querying for a specific measurement.
Hereby, you define a time window for which you want to get data by specifying startDate and endDate.
If you choose both parameters so that there are no records matching your criterion in the data lake, the API returns no data series in the response like the whole measurement would not exist.

How to reproduce?

Query the API endpoint /api/v4/datalake/measurements/<identifier> and extend the query by ?startDate=valueStart&endDate=valueEnd.
Choose valueStart and valueEnd in such way that there are no entries for targeted measurement in the corresponding time frame.
Eventually, the API returns a response with no data series indicating the whole measurement does not exist.

Expected behavior

Return the metadata of the data series but with an empty array for rows so that it clearly indicates that the actual measurement exists but there is to data available for the given query.

Additional technical information

No response

Are you willing to submit a PR?

None

[SteveYurongSu]

I'd like to take a look :)

Please assign it to me @bossenti

[SteveYurongSu]

I have done some experiments these days and found that the reason why the API returns a response indicating the whole measurement does not exist when no data between startDate and endDate:

The InfluxDB client always returns a response with no metadata when querying a timeline with no data between startDate and endDate (even if the timeline exists).

So, there seems to be some difficulty in achieving the expected behavior. In fact, I have some immature solutions in my mind. But in my solutions, at least one query call of Influxdb needs to be added in DataExplorerQueryV4#executeQuery, which may also cause additional problems...

I'm not sure what to do next now. @bossenti What do you think? 😂😂

[bossenti]

Thanks for investigating @SteveYurongSu!

Hm, if that's the standard behavior of the influx client, this might be fine as it is🤔

What would be the expected behavior for you?

[SteveYurongSu]

In order to confirm whether the behavior of InfluxDB is reasonable, I checked the behavior of IoTDB (v0.13.4) when querying a existed timeline with no data between startDate and endDate, and finally found that their behavior is really different.

The IoTDB server returned the metadata of the timeline but with an empty array for rows in result dataset. It clearly indicated that the actual timelines exist but there was no data available for the given query.

The behavior of IoTDB was what exactly we expected for. 🤔

Steps to check the behavior of IoTDB:

IoTDB> insert into root.sg.d(time, s1,s2) values (0, 1, 2)
Msg: The statement is executed successfully.
IoTDB> insert into root.sg.d(time, s1,s2) values (1, 1, 2)
Msg: The statement is executed successfully.
IoTDB> insert into root.sg.d(time, s1,s2) values (2, 1, 2)
Msg: The statement is executed successfully.
IoTDB> insert into root.sg.d(time, s1,s2) values (30, 1, 2)
Msg: The statement is executed successfully.
IoTDB> insert into root.sg.d(time, s1,s2) values (40, 1, 2)
Msg: The statement is executed successfully.
IoTDB> insert into root.sg.d(time, s1,s2) values (50, 1, 2)
Msg: The statement is executed successfully.
IoTDB> insert into root.sg.d(time, s1,s2) values (60, 1, 2)
Msg: The statement is executed successfully.

IoTDB> show timeseries
+------------+-----+-------------+--------+--------+-----------+----+----------+--------+-------------------+
|  timeseries|alias|storage group|dataType|encoding|compression|tags|attributes|deadband|deadband parameters|
+------------+-----+-------------+--------+--------+-----------+----+----------+--------+-------------------+
|root.sg.d.s1| null|      root.sg|   FLOAT| GORILLA|     SNAPPY|null|      null|    null|               null|
|root.sg.d.s2| null|      root.sg|   FLOAT| GORILLA|     SNAPPY|null|      null|    null|               null|
+------------+-----+-------------+--------+--------+-----------+----+----------+--------+-------------------+
Total line number = 2
It costs 0.042s

IoTDB> select ** from root
+-----------------------------+------------+------------+
|                         Time|root.sg.d.s1|root.sg.d.s2|
+-----------------------------+------------+------------+
|1970-01-01T08:00:00.000+08:00|         1.0|         2.0|
|1970-01-01T08:00:00.001+08:00|         1.0|         2.0|
|1970-01-01T08:00:00.002+08:00|         1.0|         2.0|
|1970-01-01T08:00:00.030+08:00|         1.0|         2.0|
|1970-01-01T08:00:00.040+08:00|         1.0|         2.0|
|1970-01-01T08:00:00.050+08:00|         1.0|         2.0|
|1970-01-01T08:00:00.060+08:00|         1.0|         2.0|
+-----------------------------+------------+------------+
Total line number = 7
It costs 0.073s

IoTDB> select s1, s2 from root.sg.d where time > 10 and time < 20
+----+------------+------------+
|Time|root.sg.d.s1|root.sg.d.s2|
+----+------------+------------+
+----+------------+------------+
Empty set.
It costs 0.103s

IoTDB> select s1, s2, s3 from root.sg.d where time > 10 and time < 20
+----+------------+------------+
|Time|root.sg.d.s1|root.sg.d.s2|
+----+------------+------------+
+----+------------+------------+
Empty set.
It costs 0.012s

IoTDB> select s1, s2, s3 from root.sg.d where time > 10
+-----------------------------+------------+------------+
|                         Time|root.sg.d.s1|root.sg.d.s2|
+-----------------------------+------------+------------+
|1970-01-01T08:00:00.030+08:00|         1.0|         2.0|
|1970-01-01T08:00:00.040+08:00|         1.0|         2.0|
|1970-01-01T08:00:00.050+08:00|         1.0|         2.0|
|1970-01-01T08:00:00.060+08:00|         1.0|         2.0|
+-----------------------------+------------+------------+
Total line number = 4
It costs 0.012s

On the other hand, I think it may be ok if InfluxDB's standard behavior does not affect the implementation of streampipes. What do you think? @bossenti

[bossenti]

Okay good to know 🤔
Frankly, I would refrain from building here something custom to get the expected behavior since we might exchange the influxdb in future...
Let's start a discussion about this on the mailing list soon 🙂
So if you are fine with it @SteveYurongSu I would close this as wont fix.

[tenthe]

+1 for starting a discussion about the pros and cons of inlfluxdb and comparing it with iotdb

[SteveYurongSu]

So if you are fine with it @SteveYurongSu I would close this as wont fix.

I'm fine with the influxdb's behaviour. Let's close it as wont-fix. 🙂 @bossenti

+1 for starting a discussion about the pros and cons of inlfluxdb and comparing it with iotdb

+1 from my side too :) @tenthe