How can we reliably break ties when two duplicate records share the exact same timestamp?
Adding secondary and tertiary ordering criteria (like sequence_id or payload completeness) guarantees deterministic ranking.
High-frequency financial trading events where multiple updates arrive within the same millisecond.
w = Window.partitionBy("trade_id").orderBy(col("timestamp").desc(), col("version").desc(), col("payload_size").desc())
df_single_trade = df.withColumn("rn", row_number().over(w)).filter(col("rn") == 1).drop("rn")Practice typing production-grade PySpark code for Tie-Breaking with Compound Window Ordering.