File size: 3,729 Bytes
2c3c408 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 | # incomplete_iteration.py
#
# LICENSE
#
# The MIT License
#
# Copyright (c) 2020 TileDB, Inc.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# DESCRIPTION
#
# Please see the TileDB documentation for more information:
# https://docs.tiledb.com/main/how-to/arrays/reading-arrays/incomplete-queries
#
# When run, this program will create a 1D dense array, write some data
# to it, and read slices back by iteration over incomplete queries.
#
import numpy as np
import tiledb
def check_dataframe_deps():
pd_error = """Pandas version >= 1.0 and < 3.0 required for dataframe functionality.
Please `pip install pandas>=1.0,<3.0` to proceed."""
try:
import pandas as pd
except ImportError:
raise Exception(pd_error)
from packaging.version import Version
if Version(pd.__version__) < Version("1.0") or Version(pd.__version__) >= Version(
"3.0.0.dev0"
):
raise Exception(pd_error)
# Name of the array to create.
array_name = "incomplete_iteration"
def create_array():
# The array will be 100 cells with dimensions "x".
dom = tiledb.Domain(tiledb.Dim(name="x", domain=(0, 99), tile=100, dtype=np.int64))
# The array will be dense with a single string typed attribute "a"
schema = tiledb.ArraySchema(
domain=dom, sparse=True, attrs=[tiledb.Attr(name="a", dtype=str)]
)
# Create the (empty) array on disk.
tiledb.SparseArray.create(array_name, schema)
def write_array():
# Open the array and write to it.
with tiledb.open(array_name, mode="w") as A:
extent = A.schema.domain.dim("x").domain
ncells = extent[1] - extent[0] + 1
# Data is the Latin alphabet with varying repeat lengths
data = [chr(i % 26 + 97) * (i % 52) for i in range(ncells)]
# Coords are the dimension range
coords = np.arange(extent[0], extent[1] + 1)
A[coords] = data
def read_array_iterated():
# in order to force iteration, restrict the buffer sizes
# this setting gives 5 iterations for the example data
init_buffer_bytes = 800
cfg = tiledb.Config(
{
"py.init_buffer_bytes": init_buffer_bytes,
"py.exact_init_buffer_bytes": "true",
}
)
with tiledb.open(array_name, config=cfg) as A:
# iterate over results as a dataframe
iterable = A.query(return_incomplete=True).df[:]
for i, result in enumerate(iterable):
print(f"--- result {i} is a '{type(result)}' with size {len(result)}")
print(result)
print("---")
print(f"Query completed after {i} iterations")
check_dataframe_deps()
create_array()
write_array()
read_array_iterated()
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