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[ETL-683] Increase memory of raw lambda #140

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merged 2 commits into from
Sep 12, 2024
Merged

[ETL-683] Increase memory of raw lambda #140

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58c6f2d
Increase memory of raw lambda
philerooski Sep 10, 2024
58b2078
add raw lambda tests to ci/cd
philerooski Sep 11, 2024
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2 changes: 2 additions & 0 deletions .github/workflows/upload-and-deploy.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -132,11 +132,13 @@ jobs:
- name: Install additional python dependency
run: |
pipenv install ecs_logging~=2.0
pipenv install pytest-datadir
- name: Test lambda scripts with pytest
run: |
pipenv run python -m pytest tests/test_s3_event_config_lambda.py -v
pipenv run python -m pytest tests/test_s3_to_glue_lambda.py -v
pipenv run python -m pytest -v tests/test_lambda_raw.py
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Nit: Depending on if this gets merged first or mine (may be a slight merge conflict), but i think you can link the tests like:

- name: Test scripts with pytest (lambda, etc.)
        run: |
          pipenv run python -m pytest \
            tests/test_s3_event_config_lambda.py \
            tests/test_s3_to_glue_lambda.py \
            tests/test_lambda_dispatch.py \
            tests/test_consume_logs.py \
            tests/test_lambda_raw.py -v

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Eh, it's better for the commands to be discrete and explicit, imo. I'm not sure if the behavior is the same running the tests one at a time (separate pipenv run...) vs running all the tests at one time (a single pipenv run...). But if there are advantages (other than brevity) I'm open to running all the tests at one time.

- name: Test dev synapse folders for STS access with pytest
run: >
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61 changes: 31 additions & 30 deletions src/lambda_function/raw/app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -211,35 +211,37 @@ def yield_compressed_data(object_stream: io.BytesIO, path: str, part_threshold=N
part_threshold = 8 * 1024 * 1024
with zipfile.ZipFile(object_stream, "r") as zip_stream:
with zip_stream.open(path, "r") as json_stream:
compressed_data = io.BytesIO()
# analogous to the part number of a multipart upload
chunk_number = 1
with gzip.GzipFile(
filename=os.path.basename(path),
fileobj=compressed_data,
compresslevel=6,
mode="wb",
) as gzip_file:
# We can expect at least 10x compression, so reading/writing the
# JSON in 10*part_threshold chunks ensures we do not flush the
# gzip buffer too often, which can slow the write process significantly.
compression_factor = 10
for chunk in iter(
lambda: json_stream.read(compression_factor * part_threshold), b""
):
gzip_file.write(chunk)
# .flush() ensures that .tell() gives us an accurate byte count,
gzip_file.flush()
if compressed_data.tell() >= part_threshold:
yield compressed_data_wrapper(
compressed_data=compressed_data, chunk_number=chunk_number
)
compressed_data.seek(0)
compressed_data.truncate(0)
chunk_number = chunk_number + 1
yield compressed_data_wrapper(
compressed_data=compressed_data, chunk_number=chunk_number
)
with io.BytesIO() as compressed_data:
# analogous to the part number of a multipart upload
chunk_number = 1
with gzip.GzipFile(
filename=os.path.basename(path),
fileobj=compressed_data,
compresslevel=6,
mode="wb",
) as gzip_file:
# We can expect at least 10x compression, so reading/writing the
# JSON in 10*part_threshold chunks ensures we do not flush the
# gzip buffer too often, which can slow the write process significantly.
compression_factor = 10
for chunk in iter(
lambda: json_stream.read(compression_factor * part_threshold),
b"",
):
gzip_file.write(chunk)
# .flush() ensures that .tell() gives us an accurate byte count,
gzip_file.flush()
if compressed_data.tell() >= part_threshold:
yield compressed_data_wrapper(
compressed_data=compressed_data,
chunk_number=chunk_number,
)
compressed_data.seek(0)
compressed_data.truncate(0)
chunk_number = chunk_number + 1
yield compressed_data_wrapper(
compressed_data=compressed_data, chunk_number=chunk_number
)


def compressed_data_wrapper(compressed_data: io.BytesIO, chunk_number: int):
Expand Down Expand Up @@ -334,4 +336,3 @@ def main(event: dict, s3_client: boto3.client, raw_bucket: str, raw_key_prefix:
logger.info(
f"Complete multipart upload response: {completed_upload_response}"
)
return completed_upload_response
2 changes: 1 addition & 1 deletion src/lambda_function/raw/template.yaml
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Expand Up @@ -52,7 +52,7 @@ Resources:
Handler: app.lambda_handler
Runtime: !Sub "python${LambdaPythonVersion}"
Role: !Ref RoleArn
MemorySize: 1024
MemorySize: 1769
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@rxu17 rxu17 Sep 11, 2024 •
edited
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Nit: Something i was thinking of but do we want to make this a variable instead? So the develop version of the lambda can declare a smaller memory size than the prod version since it won't use as much? Or were you running into this for both?

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@philerooski philerooski Sep 11, 2024 •
edited
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I don't think there's much benefit. This is not an expensive function to run, so no harm in keeping the configurations the same.

EphemeralStorage:
Size: 2048
Timeout: 900
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2 changes: 1 addition & 1 deletion tests/test_lambda_raw.py
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Expand Up @@ -4,7 +4,7 @@
import zipfile

import boto3
import pytest
import pytest # requires pytest-datadir to be installed
from moto import mock_s3

import src.lambda_function.raw.app as app
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