Understanding Stringified Arrays in BigQuery
A common challenge faced in data manipulation within BigQuery is dealing with stringified arrays. These are arrays represented as strings, often encountered when data is imported from various sources or when dealing with JSON data. When working with arrays in BigQuery, it’s important to ensure that the stringified data is in a valid JSON format. Invalid formats can lead to errors during conversion. Additionally, when dealing with large datasets, consider the performance impact and optimize your queries accordingly.
A stringified array is essentially a string that represents an array format. For example, a stringified array might look like "[\"apple\", \"banana\", \"cherry\"]". While this representation preserves the array structure, it limits the functionality and efficiency of data operations that can be performed in BigQuery.
The Need for Conversion
Converting stringified arrays into actual arrays is crucial for efficient data processing. Arrays allow for more complex operations and analyses, such as element-wise manipulation, which are not feasible with stringified data. Moreover, converting to arrays enables the use of BigQuery’s array functions, enhancing data analysis capabilities.
Step-by-Step Guide to Convert Stringified Arrays to Arrays
To convert a stringified array into an actual array in BigQuery, we primarily use the JSON_EXTRACT_ARRAY function. This function is designed to parse a JSON formatted string and extract an array from it.
Real-World Example
Consider a dataset where a column, stringified_fruits, contains stringified arrays of fruit names. The goal is to convert these stringified arrays into actual BigQuery arrays for further analysis.
Here’s a sample dataset for demonstration:
| id | stringified_fruits |
|---|---|
| 1 | “[“apple”, “banana”]” |
| 2 | “[“cherry”, “date”, “fig”]” |
| 3 | “[]” |
Code Example
To convert the stringified_fruits column into an array, we can use the following SQL query:
SELECT
id,
JSON_EXTRACT_ARRAY(stringified_fruits) AS fruits_array
FROM
`freshers.sampledata.freshers_table`
This query uses JSON_EXTRACT_ARRAY to parse each stringified array in the stringified_fruits column. The result is a new column, fruits_array, containing the converted arrays.
Sample code with test data
WITH sample_data AS (
SELECT 1 AS id, "[\"apple\", \"banana\"]" AS stringified_fruits
UNION ALL
SELECT 2, "[\"cherry\", \"date\", \"fig\"]"
UNION ALL
SELECT 3, "[]"
)
SELECT
id,
JSON_EXTRACT_ARRAY(stringified_fruits) AS fruits_array
FROM
sample_data
In this example:
The WITH clause creates a temporary table sample_data with columns id and stringified_fruits.
The UNION ALL statements add rows to sample_data with hard-coded values for id and stringified_fruits.
The main SELECT statement then performs the conversion on this temporary table, extracting the stringified arrays into actual arrays.
Output
id fruits.array
1 "apple"
"banana"
2 "cherry"
"date"
Tig’
3 0 rowsBigQuery import urls to refer
