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A data analytics team is ingesting e-commerce transaction records from Cloud Storage into BigQuery. Each transaction record contains complex hierarchical information, including nested customer contact details and a repeated list of purchased product line items.
Which file format should the team use to load this data while natively preserving its nested and repeated data structure?
Newline-delimited JSON (often referred to as ndjson or JSON Lines) is a semi-structured, text-based data interchange format where each individual line in a file contains a complete, valid JSON object. In data analytics and ingestion platforms like BigQuery, newline-delimited JSON is the standard JSON format used for batch data loads and streaming ingestion because each record is self-contained and separated by a newline character (\n).
"items": [...]), which BigQuery represents as REPEATED (ARRAY) fields. This allows multiple purchased items to be stored directly inside a single transaction record without requiring denormalization or separate child tables.Unlike flat, tabular formats such as CSV that only represent two-dimensional rows and columns, newline-delimited JSON allows complex, multi-tiered business objects to be ingested into BigQuery in their natural structure. This avoids the overhead of flattening arrays or maintaining multiple related tables, making it the ideal choice for hierarchical transaction logs.
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