fix(test): Update schema for broken ConnImplBenchmark test

[o-shevchenko]

I'm trying to use the executeSelect API and faced extremely slow reading. I tried to use ConnImplBenchmark but noticed that the Shema was changed, and the test didn't work.

bigquery-public-data.new_york_taxi_trips.tlc_yellow_trips_2017

Summary of Changes Added Fields: airport_fee, data_file_year, data_file_month. Removed Fields: dropoff_longitude, dropoff_latitude, pickup_longitude, pickup_latitude.

After fixing the test I can confirm that we have similar speed results for our use cases. Reading 100_000 rows takes ~15-20 seconds, which is extremely slow.

 Running
ROW 100000 Time: 14978 ms
ROW 200000 Time: 16409 ms
ROW 300000 Time: 16966 ms
ROW 400000 Time: 15963 ms
ROW 500000 Time: 17480 ms

I'm not sure if there was any performance degradation recently since I can't find any expected numbers. It's hard to read this benchmark: https://cloud.google.com/blog/topics/developers-practitioners/introducing-executeselect-client-library-method-and-how-use-it/ According to this image, reading of 1_000_000 rows should take ~1sec

That's what I've got on my machine:

Benchmark                                            (rowLimit)  Mode  Cnt       Score       Error  Units
ConnImplBenchmark.iterateRecordsUsingReadAPI             500000  avgt    3   76549.893 ± 14496.839  ms/op
ConnImplBenchmark.iterateRecordsUsingReadAPI            1000000  avgt    3  154957.127 ± 25916.110  ms/op
ConnImplBenchmark.iterateRecordsWithBigQuery_Query       500000  avgt    3   82508.807 ± 17930.275  ms/op
ConnImplBenchmark.iterateRecordsWithBigQuery_Query      1000000  avgt    3  165717.219 ± 86960.648  ms/op
ConnImplBenchmark.iterateRecordsWithoutUsingReadAPI      500000  avgt    3   84504.175 ± 36823.590  ms/op
ConnImplBenchmark.iterateRecordsWithoutUsingReadAPI     1000000  avgt    3  165142.367 ± 99899.991  ms/op

I've opened an issue: https://github.com/googleapis/java-bigquerystorage/issues/2764

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[o-shevchenko]

@alvarowolfx Could you please help with the review and performance evaluation? Thanks!

[o-shevchenko]

@alvarowolfx, did you have a chance to look into it?

[alvarowolfx]

@PhongChuong can you take a look on this one ?