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etlantic-pyspark

PySpark reference execution plugin and portable transform compiler for ETLantic 0.53.

Note: This plugin and ETLantic core use Beta classifiers for documented single-tenant pilots. Classifiers are not an enterprise SLA.

Install

pip install etlantic-pyspark
# Optional Delta Lake support:
pip install "etlantic-pyspark[delta]"

Portable transform compiler

from etlantic import Profile

Profile(
    name="spark-local",
    spark_engine="pyspark",
    portable_transform_policy="require",
)

Entry point: etlantic.transform_compilersetlantic_pyspark:create_transform_compiler.

Claims portable-relational-kernel/1 and portable-relational/1. Lowers dtcs.transform-plan/2 to native Spark DataFrame/Column expressions. This is the recommended transformation path and remains eligible for adaptive execution. Automatic Python/Pandas UDF fallback is forbidden.

Native Spark plugin

Register @Transformation.implementation("pyspark") handlers only for Spark behavior outside the portable compiler's claims. They take Spark DataFrames (or lists of contract models), return Spark DataFrames, pin the step to PySpark, and are not eligible for adaptive execution.

Native capabilities

  • Lazy Spark region fusion with preserved logical identities
  • Local Spark provider (local[*]) — secrets resolved only at session acquire
  • Native-expression preference with UDF policy diagnostics
  • Contract ↔ Spark schema mapping (lossy/unknown never guessed)
  • Valid/invalid row separation
  • Delta-compatible write intents (append/overwrite/merge) when Delta is enabled
  • Structured Streaming foundation (experimental)

Native UDF policy stays separate. Default CI uses sparkless; set SPARKLESS_TEST_MODE=pyspark for real JVM Catalyst checks.

Not included: managed cloud providers (Databricks/EMR/Connect).

PySpark tutorial · Compatibility · Source · Issues

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