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mack
mack provides a variety of helper methods that make it easy for you to perform common Delta Lake operations.
Setup
Install mack with pip install mack
.
Here's an example of how you can perform a Type 2 SCD upsert with a single line of code using Mack:
import mack
mack.type_2_scd_upsert(path, updatesDF, "pkey", ["attr1", "attr2"])
Type 2 SCD Upserts
This library provides an opinionated, conventions over configuration, approach to Type 2 SCD management. Let's look at an example before covering the conventions required to take advantage of the functionality.
Suppose you have the following SCD table with the pkey
primary key:
+----+-----+-----+----------+-------------------+--------+
|pkey|attr1|attr2|is_current| effective_time|end_time|
+----+-----+-----+----------+-------------------+--------+
| 1| A| A| true|2019-01-01 00:00:00| null|
| 2| B| B| true|2019-01-01 00:00:00| null|
| 4| D| D| true|2019-01-01 00:00:00| null|
+----+-----+-----+----------+-------------------+--------+
You'd like to perform an upsert with this data:
+----+-----+-----+-------------------+
|pkey|attr1|attr2| effective_time|
+----+-----+-----+-------------------+
| 2| Z| null|2020-01-01 00:00:00| // upsert data
| 3| C| C|2020-09-15 00:00:00| // new pkey
+----+-----+-----+-------------------+
Here's how to perform the upsert:
mack.type_2_scd_upsert(path, updatesDF, "pkey", ["attr1", "attr2"])
Here's the table after the upsert:
+----+-----+-----+----------+-------------------+-------------------+
|pkey|attr1|attr2|is_current| effective_time| end_time|
+----+-----+-----+----------+-------------------+-------------------+
| 2| B| B| false|2019-01-01 00:00:00|2020-01-01 00:00:00|
| 4| D| D| true|2019-01-01 00:00:00| null|
| 1| A| A| true|2019-01-01 00:00:00| null|
| 3| C| C| true|2020-09-15 00:00:00| null|
| 2| Z| null| true|2020-01-01 00:00:00| null|
+----+-----+-----+----------+-------------------+-------------------+
You can leverage the upsert code if your SCD table meets these requirements:
- Contains a unique primary key column
- Any change in an attribute column triggers an upsert
- SCD logic is exposed via
effective_time
,end_time
andis_current
column (you can also use date or version columns for SCD upserts)
Kill duplicates
The kill_duplicate
function completely removes all duplicate rows from a Delta table.
Suppose you have the following table:
+----+----+----+
|col1|col2|col3|
+----+----+----+
| 1| A| A| # duplicate
| 2| A| B|
| 3| A| A| # duplicate
| 4| A| A| # duplicate
| 5| B| B| # duplicate
| 6| D| D|
| 9| B| B| # duplicate
+----+----+----+
Run the kill_duplicates
function:
mack.kill_duplicates(deltaTable, ["col2", "col3"])
Here's the ending state of the table:
+----+----+----+
|col1|col2|col3|
+----+----+----+
| 2| A| B|
| 6| D| D|
+----+----+----+
Drop duplicates with Primary Key
The drop_duplicates_pkey
function removes all but one duplicate row from a Delta table.
Warning: You have to provide a primary column that must contain unique values, otherwise the method will default to kill the duplicates.
If you can not provide a unique primary key, you can use the drop_duplicates
method.
Suppose you have the following table:
+----+----+----+----+
|col1|col2|col3|col4|
+----+----+----+----+
| 1| A| A| C| # duplicate1
| 2| A| B| C|
| 3| A| A| D| # duplicate1
| 4| A| A| E| # duplicate1
| 5| B| B| C| # duplicate2
| 6| D| D| C|
| 9| B| B| E| # duplicate2
+----+----+----+----+
Run the drop_duplicates
function:
mack.drop_duplicates_pkey(delta_table=deltaTable, primary_key="col1", duplication_columns=["col2", "col3"])
Here's the ending state of the table:
+----+----+----+----+
|col1|col2|col3|col4|
+----+----+----+----+
| 1| A| A| C|
| 2| A| B| C|
| 5| B| B| C|
| 6| D| D| C|
+----+----+----+----+
Drop duplicates
The drop_duplicates
function removes all but one duplicate row from a Delta table. It behaves exactly like the drop_duplicates
DataFrame API.
Warning: This method is overwriting the whole table, thus very inefficient. If you can, use the drop_duplicates_pkey
method instead.
Suppose you have the following table:
+----+----+----+----+
|col1|col2|col3|col4|
+----+----+----+----+
| 1| A| A| C| # duplicate
| 1| A| A| C| # duplicate
| 2| A| A| C|
+----+----+----+----+
Run the drop_duplicates
function:
mack.drop_duplicates_pkey(delta_table=deltaTable, duplication_columns=["col1"])
Here's the ending state of the table:
+----+----+----+----+
|col1|col2|col3|col4|
+----+----+----+----+
| 1| A| A| C| # duplicate
| 2| A| A| C| # duplicate
+----+----+----+----+
Copy table
The copy_table
function copies an existing Delta table.
When you copy a table, it gets recreated at a specified target. This target could be a path or a table in a metastore.
Copying includes:
- Data
- Partitioning
- Table properties
Copying does not include the delta log, which means that you will not be able to restore the new table to an old version of the original table.
Here's how to perform the copy:
mack.copy_table(delta_table=deltaTable, target_path=path)
Append data without duplicates
The append_without_duplicates
function helps to append records to a existing Delta table without getting duplicates appended to the
record.
Suppose you have the following Delta table:
+----+----+----+
|col1|col2|col3|
+----+----+----+
| 1| A| B|
| 2| C| D|
| 3| E| F|
+----+----+----+
Here is data to be appended:
+----+----+----+
|col1|col2|col3|
+----+----+----+
| 2| R| T| # duplicate col1
| 8| A| B|
| 10| X| Y|
+----+----+----+
Run the append_without_duplicates
function:
mack.append_without_duplicates(deltaTable, append_df, ["col1"])
Here's the ending result:
+----+----+----+
|col1|col2|col3|
+----+----+----+
| 1| A| B|
| 2| C| D|
| 3| E| F|
| 8| A| B|
| 10| X| Y|
+----+----+----+
Notice that the duplicate col1
value was not appended. If a normal append operation was run, then the Delta table would contain two rows
of data with col1
equal to 2.
Delta File Sizes
The delta_file_sizes
function returns a dictionary that contains the total size in bytes, the amount of files and the average file size
for a given Delta Table.
Suppose you have the following Delta Table, partitioned by col1
:
+----+----+----+
|col1|col2|col3|
+----+----+----+
| 1| A| A|
| 2| A| B|
+----+----+----+
Running mack.delta_file_sizes(delta_table)
on that table will return:
{"size_in_bytes": 1320, "number_of_files": 2, "average_file_size_in_bites": 660}
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