The following code crashes with a seg fault:
In [1]: import tiledb
In [2]: loaded = tiledb.open('/path/to/my/data')
In [3]: loaded.df[:]
Segmentation fault (core dumped)
Are there any suggested approaches to debugging this without building the c lib (using metadata available in python)?
Alternatively, I will be happy to see suggested approaches for incremental construction of time-series data with schema evolution.
Steps to reproduce the array:
import numpy as np
import pandas as pd
import tiledb
array_uri = '/path/to/my/data'
days = pd.date_range('2021-01-01T10:00:00', '2021-01-10')
cols = [f'COL_{i}' for i in range(5)]
data = pd.DataFrame(np.random.randn(len(days), len(cols)), index=days, columns=cols)
data.index.name = 'date'
tiledb.from_pandas(array_uri, data.reset_index(), index_col=[0], sparse=False, debug=True)
loaded = tiledb.open(array_uri)
days = pd.date_range('2021-01-10T10:00:00', '2021-01-15')
cols = cols + ['COL_5']
data = pd.DataFrame(np.random.randn(len(days), len(cols)), index=days, columns=cols)
data.index.name = 'date'
ctx = tiledb.default_ctx()
se = tiledb.ArraySchemaEvolution(ctx)
se.add_attribute(tiledb.Attr(data.columns[-1], dtype=data[data.columns[-1]].dtype))
se.array_evolve(array_uri)
tiledb.from_pandas(array_uri, data.reset_index(), index_col=[0], mode='append', row_start_idx=loaded.nonempty_domain()[0][1] + 1)
loaded = tiledb.open(array_uri)
loaded.df[:]