Flux stops reading results on first shard with no data

[Techmaster21]

Steps to reproduce:

1. Download tests.zip, it contains two annotated csv files, test1.csv and test4.csv
2. Add test1.csv to influxdb using influx write Note that there are 80 records in this file spanning a year. Confirm that there are now 80 records in this measurement using the following query

from(bucket: "test")
  |> range(start: -1y)
  |> filter(fn: (r) => r["_measurement"] == "Measurement1")
  |> drop(columns: ["team", "scope"])
  |> count()

3. Now add test4.csv to influxdb. Run the query above again. Note that there are now only 18 records, even though test4 only adds records to Measurement4.

Expected behavior:
When two records have the same timestamp and tags, I expect one to overwrite the other without affecting other measurements.

Actual behavior:
One overwrites the other, but then messes up data from other measurements.

Environment info:

• System info: Linux 4.19.76-linuxkit x86_64
• InfluxDB version: InfluxDB 2.0.1 (git: 37cc047) build_date: 2020-11-11T03:53:31Z
• Other relevant environment details: Running using the docker image on Windows 10 using HyperV containers

[danxmoran]

Reproduced, investigating now...

[danxmoran]

Strange data point: If I remove drop(columns: ["team", "scope"]) from the query, then the output after writing test4 is:

Result: _result
Table: keys: [_start, _stop, _field, _measurement]
                   _start:time                      _stop:time           _field:string     _measurement:string                  _value:int
------------------------------  ------------------------------  ----------------------  ----------------------  --------------------------
2019-11-17T11:43:41.599734000Z  2020-11-16T17:43:41.599734000Z                  timing            Measurement1                          18
Table: keys: [_start, _stop, _field, _measurement]
                   _start:time                      _stop:time           _field:string     _measurement:string                  _value:int
------------------------------  ------------------------------  ----------------------  ----------------------  --------------------------
2019-11-17T11:43:41.599734000Z  2020-11-16T17:43:41.599734000Z                  timing            Measurement1                          33
Table: keys: [_start, _stop, _field, _measurement]
                   _start:time                      _stop:time           _field:string     _measurement:string                  _value:int
------------------------------  ------------------------------  ----------------------  ----------------------  --------------------------
2019-11-17T11:43:41.599734000Z  2020-11-16T17:43:41.599734000Z                  timing            Measurement1                          29

The counts sum up to 80

[danxmoran]

@Techmaster21 I'm not sure if this is the only error, but I think part of the problem is that the headers in your CSVs are malformed, so the CSV->LP converter is dropping a lot of data before sending to influxd. Could you try replacing the initial commas in your headers with spaces? i.e.

- #group,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE
+ #group FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,TRUE,TRUE,TRUE

[Techmaster21]

@danxmoran I tried that and got the following error when attempting to add the CSV to influx:

 info    WARNING: at most one dateTime column is expected, 'table' column is ignored
Error: Failed to write data: line 5: column '_time': strconv.ParseFloat: parsing "2020-03-12T18:04:08.95Z": invalid syntax.

I would like to point out that the csv files I included are directly from the "download csv" button in the UI - with some simplification to find a more minimal case, but I never touched the headers.

Furthermore, I have some new information that suggests this is unrelated to CSV issues or the existence of a duplicate timestamp.
If you add the following to a bucket (I used the UI -> buckets -> add data -> line protocol -> set to milliseconds -> enter manually)

Measurement1 timing=56.96377314814815 1597944509870
Measurement1 timing=0.0 1598992534397
Measurement1 timing=12.91412037037037 1597862094673
Measurement1 timing=33.96895833333333 1601412291807
Measurement1 timing=0.013784722222222223 1598991442593
Measurement1 timing=21.070949074074075 1598373708313
Measurement1 timing=9.086516203703704 1597869159047
Measurement1 timing=13.835648148148149 1597944002557
Measurement1 timing=42.023587962962964 1592323982273
Measurement1 timing=33.82604166666667 1598373617570
Measurement1 timing=50.13054398148148 1592324004273
Measurement1 timing=113.10400462962963 1604520205927
Measurement1 timing=0.999988425925926 1603806142050

You get all thirteen datapoints when running the following:

from(bucket: "test")
  |> range(start: -1y)
  |> filter(fn: (r) => r["_measurement"] == "Measurement1")
  |> filter(fn: (r) => r["_field"] == "timing")

However if you add the following two datapoints to the same bucket

Measurement2 timing=0.9970833333333333 1593012434807
Measurement2 timing=124.21572916666666 1594822596920

Then re-running the previous query results in only 2 datapoints.

Also to note, my original issue was not occurring using line protocol or CSV files, but rather the Java client, but in the interest of providing a minimal example (and the fact that the results are consistent regardless of the means of entering the data), I converted it to a CSV

[danxmoran]

Thanks for all the extra info, I'd better file an extra issue to either fix the CSV docs or fix the download logic 😓 I'll keep digging on this weird behavior

[danxmoran]

I'm unable to reproduce using influx write and influx query. Will try via the UI next. Was able to reproduce by using --precision ms

[danxmoran]

Reproduced in the UI. Was also able to reproduce via the CLI if I used the right precision.

[stuartcarnie]

Hi @Techmaster21, thanks for the report!

For completeness, I want to clarify some details based on the tests.zip file.

• The two CSV files import data in to separate measurements.

• test1.csv imports 80 unique records into Measurement1

• test4.csv imports 38 records, however, lines 19 and 20 are the same timestamp and series:

  ,result,table,_start,_stop,_time,_value,_field,_measurement,closed,scope,team
  ,,0,2019-11-14T12:01:16.341288Z,2020-11-13T18:01:16.341288Z,2020-08-27T17:49:59.56Z,7.235046296,timing,Measurement4,FALSE,MyScope,MyTeam
  ,,0,2019-11-14T12:01:16.341288Z,2020-11-13T18:01:16.341288Z,2020-08-27T17:49:59.56Z,6.945694444,timing,Measurement4,FALSE,MyScope,MyTeam
  

  The result is 37 rows into Measurement4.

I queried the data with Flux and then InfluxQL to reduce the likeliness that ingest is an issue.

Flux query of Measurement1:

Returned a sum of 18. As @danxmoran mentioned earlier (and I can confirm) removing the drop returns three unique rows that sum to the correct amount.

curl -H 'content-type:application/vnd.flux' -H "Authorization: Token ${INFLUX_TOKEN}" ${INFLUX_HOST}/api/v2/query\?org\=my-org --data-binary 'from(bucket: "my-bucket") |> range(start: -1y) |> filter(fn: (r) => r._measurement == "Measurement1") |> drop(columns: ["team", "scope"]) |> count()'

,result,table,_start,_stop,_field,_measurement,_value
,_result,0,2019-11-17T21:48:16.04191Z,2020-11-17T03:48:16.04191Z,timing,Measurement1,18

Flux query of Measurement4:

Returned a sum of 1

curl -H 'content-type:application/vnd.flux' -H "Authorization: Token ${INFLUX_TOKEN}" ${INFLUX_HOST}/api/v2/query\?org\=my-org --data-binary 'from(bucket: "my-bucket") |> range(start: -1y) |> filter(fn: (r) => r._measurement == "Measurement4") |> drop(columns: ["team", "scope"]) |> count()'

,result,table,_start,_stop,_field,_measurement,_value
,_result,0,2019-11-17T21:53:08.244168Z,2020-11-17T03:53:08.244168Z,timing,Measurement4,1

I re-ran the queries with InfluxQL and can confirm the data was imported and written correctly.

InfluxQL query of Measurement1:

curl -u ${INFLUXV1_USER}:${INFLUXV1_PASS} -H Content-Type:application/vnd.influxql -H Accept:text/plain ${INFLUX_HOST}/query\?db=my-bucket --data-binary "select count(timing) from Measurement1"

name: Measurement1
time                          count
----                          -----
1970-01-01 00:00:00 +0000 UTC 80

InfluxQL query of Measurement4

curl -u ${INFLUXV1_USER}:${INFLUXV1_PASS} -H "jaeger-debug-id: stuart" -H Content-Type:application/vnd.influxql -H Accept:text/plain ${INFLUX_HOST}/query\?db=my-bucket --data-binary "select count(timing) from Measurement4"

name: Measurement4
time                          count
----                          -----
1970-01-01 00:00:00 +0000 UTC 37