Aggregation, executed on a table projection, is much slower, than on an imported table

Code to reproduce:
```python
import pyhdk
from time import time
from numpy.random import random_integers

hdk = pyhdk.hdk.HDK()
ht = hdk.import_pydict({"a": random_integers(0, 1000, 300_000_000)})
t = time()
result1 = ht.proj("a").agg("a", "count").run()
print(f"Imported table time: {time() - t}")

ht = ht.proj("a").run()
t = time()
result2 = ht.agg("a", "count").run()
print(f"Projected table time: {time() - t}")
assert result1.to_arrow() == result2.to_arrow()
```
Output:
```
Imported table time: 0.17155766487121582
Projected table time: 18.890812397003174
```

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Aggregation, executed on a table projection, is much slower, than on an imported table #696

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Aggregation, executed on a table projection, is much slower, than on an imported table #696

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