Lineage Keeper

A lightweight lineage tool based on Spark and Delta Lake

Table of contents

• Instalation
• Basic use
• Functionalities
  • Listener function
  • load listener
  • Lineage graph viewer
  • Lineage graph writer
• Limitations
• Demo Notebook

Instalation

pip install lineage-keeper

Basic use

from lineage_keeper import load_listener, LineageViewer
load_listener(spark)

df1 = spark.read.table("db.table_1")
df2 = spark.read.table("db.table_2")

df_join = df1.join(df2, "key")

df_join.write.saveAsTable("db.join_tables")

LineageViewer(spark).viewer()

Functionalities

By default Lineage Keeper use "default._service_table_lineage_keeper" as a service table.

If wanted its possible to use a different service table.

Listener function

Manually input lineage information on the service table

LineageListener : spark sesison

listener : source DataFrame, target table

ll = LineageListener(spark)
ll.listener(df, "target_db.target_table")

load listener

Change df.write.saveAsTable to automatically input lineage information on the service table

load_listener(spark)

Lineage graph viewer

Generate a static HTML with the lineage graph

LineageViewer(spark).viewer()

Lineage graph writer

Save a static HTML with the lineage graph on disk

LineageViewer(spark).save_graph(path)

Limitations

• Its necessary to use tables sintax to read data
  • spark.read.table("db.table")
  • spark.sql("SELECT * FROM db.table")
• To use load_listener to is necessary to use df.write.saveAsTable("db.table") otherwise need to call LineageListener(spark).listener(df, "db.table")

Demo Notebook

Sample using Lineage Keeper