Streamlining AWS Lambda with DuckDB for Dynamic Data Handling

gistfile1.python

import json
import os
import duckdb
import boto3
import datetime
from typing import Any, Dict


def construct_prepared_sql_and_params(sql_template, bind_params):
    single_value_params = {k: v for k, v in bind_params.items() if not isinstance(v, list)}
    list_params = {k: v for k, v in bind_params.items() if isinstance(v, list)}

    for key in single_value_params.keys():
        sql_template = sql_template.replace(f"{{{key}}}", "?")

    for key, values in list_params.items():
        placeholders = ', '.join(['?'] * len(values))
        sql_template = sql_template.replace(f"{{{key}}}", placeholders)

    flat_params = []
    for key in bind_params:
        if key in single_value_params:
            flat_params.append(single_value_params[key])
        elif key in list_params:
            flat_params.extend(list_params[key])

    return sql_template, flat_params


def serialize_dates(row):
    for key, value in row.items():
        if isinstance(value, datetime.date):
            row[key] = value.strftime('%d-%m-%Y')
    return row


def lambda_handler(event: Dict[str, Any], context):
    print("Duckdb Lambda received event: " + json.dumps(event, indent=4))
    file_name = event.get('file_name')
    sql = event.get('sql')
    bind_params = event.get('bind_params', {})
    return_type = event.get('return_type', 'List')

    s3 = boto3.client('s3')
    bucket_name = os.getenv('BUCKET_NAME')

    local_file_name = f"/tmp/{file_name}"
    os.makedirs(os.path.dirname(local_file_name), exist_ok=True)

    s3.download_file(bucket_name, file_name, local_file_name)

    conn = duckdb.connect(database=':memory:', read_only=False)
    prepared_sql = sql % local_file_name

    try:
        prepared_sql, flat_params = construct_prepared_sql_and_params(prepared_sql, bind_params)
        print(prepared_sql)
        print(f"flat_params -> {flat_params}")
        cursor = conn.execute(prepared_sql, parameters=flat_params)
        columns = [description[0] for description in cursor.description]
        fetched_results = [dict(zip(columns, row)) for row in cursor.fetchall()]

        fetched_results = [serialize_dates(row) for row in fetched_results]

        if return_type == 'Single':
            results = fetched_results[0] if fetched_results else {}
        else:
            results = fetched_results
    finally:
        conn.close()

    print("Duckdb Lambda processing completed")
    return results

this works for me.

ref: https://alexander-grun.github.io/ag-blog/duck-db-aws-lambda-layer/

TY @alexander-grun

this works for me.

ref: https://alexander-grun.github.io/ag-blog/duck-db-aws-lambda-layer/

TY @alexander-grun

To make it run on Lambda, I also need to set up home_directory. This is my simple Lambda code.

import json
import duckdb

def lambda_handler(event, context):
    print('Hi')

    duckdb_conn = duckdb.connect()

    print(f"Installing duckdb extensions. Installing httpfs.")
    duckdb_conn.sql("SET home_directory='/tmp';")
    duckdb_conn.sql("install httpfs")
    print(f"Loading  httpfs")
    duckdb_conn.sql("load httpfs")
    print('LOADED!')