How to load data from Parquet File to Firebolt

Learn how to use Airbyte to synchronize your Parquet File data into Firebolt within minutes.

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Parquet File connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Firebolt for your extracted Parquet File data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Parquet File to Firebolt in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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How to Sync to Manually

Step 1: Install Required Tools

Begin by installing the necessary tools on your local machine. You'll need Python (preferably version 3.7 or later) and the `pyarrow` library to read Parquet files, and the `firebolt-sdk` to interact with Firebolt. You can install these using pip:
```
pip install pyarrow firebolt-sdk
```

Set up and configure your connection to Firebolt. You'll need your Firebolt account credentials and the database name. Create a configuration file or set environment variables to store these securely:
```python
from firebolt.sdk import Client

client = Client(username='', password='')
connection = client.connect(database='')
```

Use `pyarrow` to read the contents of your Parquet file into a Pandas DataFrame. This allows for easy manipulation and preparation of the data:
```python
import pyarrow.parquet as pq
import pandas as pd

parquet_file = 'path/to/your/file.parquet'
table = pq.read_table(parquet_file)
df = table.to_pandas()
```

Convert the DataFrame to a list of tuples, which is a format that can be easily used for data insertion into Firebolt. Ensure that the column order matches the table schema in Firebolt:
```python
data = [tuple(x) for x in df.to_numpy()]
columns = ', '.join(df.columns)
```

If the target table does not already exist in Firebolt, you need to create it. Use the column names and types from the DataFrame to define your schema:
```python
create_table_query = f"""
CREATE TABLE IF NOT EXISTS your_table_name (
column1_name column1_type,
column2_name column2_type,
...
)
"""
connection.execute(create_table_query)
```

Insert the data into the Firebolt table. Use a parameterized query to safely insert data and avoid SQL injection:
```python
insert_query = f"INSERT INTO your_table_name ({columns}) VALUES (?, ?, ...)"
connection.executemany(insert_query, data)
```

After insertion, verify that the data has been correctly transferred by executing a simple query to check the row count or specific data checks:
```python
result = connection.execute("SELECT COUNT(*) FROM your_table_name")
print("Number of rows inserted:", result.fetchone()[0])
```

By following these steps, you can successfully move data from a Parquet file to Firebolt without relying on third-party connectors or integrations.