updating beam pipeline to use GroupByKey

This commit is contained in:
2021-09-26 20:29:11 +01:00
parent 4e3771c728
commit 8e8469579e

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@@ -2,6 +2,7 @@ import argparse
from datetime import datetime
import hashlib
import itertools
import json
import logging
import pathlib
@@ -12,17 +13,37 @@ from apache_beam.options.pipeline_options import PipelineOptions, SetupOptions
def slice_by_range(element, *ranges):
"""Slice a list with multiple ranges."""
"""
Slice a list with multiple ranges.
Args:
element : The element.
*ranges (tuple): Tuples containing a start,end index to slice the element.
E.g (0, 3), (5, 6) - Keeps columns 0,1,2,5. Drops everything else.
Returns:
list: The list sliced by the ranges
"""
return itertools.chain(*(itertools.islice(element, *r) for r in ranges))
class DropRecordsSingleEmptyColumn(beam.DoFn):
"""If a given item in a list is empty, drop this entry from the PCollection."""
def __init__(self, index):
self.index = index
def process(self, element):
"""
Drop the entire row if a given column is empty.
Args:
element : The element
Returns:
None: If the length of the column is 0, drop the element.
Yields:
element: If the length of the column isn't 0, keep the element.
"""
column = element[self.index]
if len(column) == 0:
return None
@@ -78,9 +99,9 @@ class GenerateUniqueID(beam.DoFn):
",".join(element[2:]) if not self.all_columns else ",".join(element)
)
hashed_string = hashlib.md5(unique_string.encode())
# append the hash to the end
element.append(hashed_string.hexdigest())
yield element
# add the hash as a key to the data.
new_element = (hashed_string.hexdigest(), list(element))
yield new_element
class DeduplicateByID(beam.DoFn):
@@ -91,7 +112,7 @@ class DeduplicateByID(beam.DoFn):
def process(self, element):
if len(list(element[1])) > 0:
deduplicated_element = (list(element[0]), [list(element[1])[0]])
deduplicated_element = (element[0], [list(element[1])[0]])
yield deduplicated_element
else:
yield element
@@ -102,7 +123,6 @@ class RemoveUniqueID(beam.DoFn):
def process(self, element):
element_no_id = element[-1][0]
element_no_id.pop(-1)
yield element_no_id
@@ -169,7 +189,7 @@ class ConvertDataToDict(beam.DoFn):
# Create the dict to hold all the information about the property.
json_object = {
"property_id": element[0],
"readable_address": None,
# "readable_address": None,
"flat_appartment": list(element[-1])[0][4],
"builing": list(element[-1])[0][10],
"number": list(element[-1])[0][3],
@@ -189,20 +209,20 @@ class ConvertDataToDict(beam.DoFn):
}
# Create a human readable address to go in the dict.
json_object["readable_address"] = self.get_readable_address(
[
json_object["flat_appartment"],
json_object["builing"],
f'{json_object["number"]} {json_object["street"]}',
json_object["postcode"],
],
[
json_object["locality"],
json_object["town"],
json_object["district"],
json_object["county"],
],
)
# json_object["readable_address"] = self.get_readable_address(
# [
# json_object["flat_appartment"],
# json_object["builing"],
# f'{json_object["number"]} {json_object["street"]}',
# json_object["postcode"],
# ],
# [
# json_object["locality"],
# json_object["town"],
# json_object["district"],
# json_object["county"],
# ],
# )
yield json_object
@@ -259,6 +279,7 @@ def run(argv=None, save_main_session=True):
| "Drop Empty Postcodes" >> beam.ParDo(DropRecordsSingleEmptyColumn(2))
| "Drop empty PAON if missing SAON"
>> beam.ParDo(DropRecordsTwoEmptyColumn(3, 4))
# | beam.ParDo(DebugShowColumnWithValueIn(2, "B16 0AE"))
| "Split PAON into two columns if separated by comma"
>> beam.ParDo(SplitColumn(3, ","))
)
@@ -269,7 +290,7 @@ def run(argv=None, save_main_session=True):
| "Generate unique ID for all columns"
>> beam.ParDo(GenerateUniqueID(all_columns=True))
| "Group by the ID for all columns"
>> beam.GroupBy(lambda element: element[-1])
>> beam.GroupByKey()
| "Deduplicate by the ID for all columns" >> beam.ParDo(DeduplicateByID())
)
@@ -281,7 +302,8 @@ def run(argv=None, save_main_session=True):
| "Generate unique ID ignoring price & date"
>> beam.ParDo(GenerateUniqueID())
| "Group by the ID ignoring price & date"
>> beam.GroupBy(lambda element: element[-1])
>> beam.GroupByKey()
# | beam.Map(print)
)
# Format the data into a dict.
@@ -295,6 +317,7 @@ def run(argv=None, save_main_session=True):
(
formatted
| "Combine into one PCollection" >> beam.combiners.ToList()
| "Format output" >> beam.Map(json.dumps)
| "Save to .json file"
>> beam.io.WriteToText(
file_path_prefix=known_args.output,