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feat: explicit schema for all_events bronze table #69

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feat: explicit schema for all_events bronze table #69

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d68d97d
feat: apply explicit schema to all_events bronze table
nkarpov Apr 2, 2026
f13da0b
fix: use location_id (INT) instead of location (STRING) in bronze schema
nkarpov Apr 3, 2026
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18 changes: 15 additions & 3 deletions pipelines/order_items/transformations/transformation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,12 +5,23 @@
import pyspark.sql.functions as F
from pyspark.sql.types import (
StructType, StructField, StringType, IntegerType,
DoubleType, ArrayType
DoubleType, ArrayType, TimestampType
)

# ──────────────────────────────────────────────────────────────
# 0. Bronze – raw event stream
# ──────────────────────────────────────────────────────────────
all_events_schema = StructType([
StructField("event_id", StringType()),
StructField("event_type", StringType()),
StructField("ts", TimestampType()),
StructField("gk_id", StringType()),
StructField("location_id", IntegerType()),
StructField("order_id", StringType()),
StructField("sequence", IntegerType()),
StructField("body", StringType()),
])

@dlt.table(
comment = "Raw JSON events as ingested (one file per event)."
)
Expand All @@ -19,8 +30,9 @@ def all_events():
SCHEMA = spark.conf.get("RAW_DATA_SCHEMA")
VOLUME = spark.conf.get("RAW_DATA_VOLUME")
return (
spark.readStream.format("cloudFiles")
spark.readStream.format("cloudFiles")
.option("cloudFiles.format", "json")
.schema(all_events_schema)
.load(f"/Volumes/{CATALOG}/{SCHEMA}/{VOLUME}")
)

Expand Down Expand Up @@ -54,7 +66,7 @@ def silver_order_items():
df = (
dlt.read_stream("all_events")
.filter(F.col("event_type") == "order_created")
.withColumn("event_ts", F.to_timestamp("ts")) # enforce TIMESTAMP
.withColumnRenamed("ts", "event_ts")
.withColumn("body_obj", F.from_json("body", body_schema))
.withColumn("item", F.explode("body_obj.items"))
.withColumn("extended_price", F.col("item.price") * F.col("item.qty"))
Expand Down