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Version 1.1.0

This release encompasses all the features introduced in 1.0.0 (see whats_new_v1_0_0) and introduces additional functionalities along with more precise docstrings.

Options

set_option() function has more options:

  • max_cellwidth: Maximum width of any VerticaPy table’s cell.

  • max_tableheight: Maximum height of VerticaPy tables.

  • theme: Theme used to display the VerticaPy objects (light, dark or sphinx).

  • verbosity: This will set the amount of information to display while executing VerticaPy functions.

Note

There are four levels of verbosity:

  • 0 (silent)

  • 1 (warning)

  • 2 (info)

  • 3 (debug)

Machine Learning

PLS Regression

Partial Least Squares (PLS) regression has been added to VerticaPy.

This integration will enhance VerticaPy’s analytics capabilities, particularly benefiting Vertica customers who have expressed interest in utilizing PLS regression.

For more details, please look at PLSRegression

Example use:

from verticapy.machine_learning.vertica import PLSRegression

model = PLSRegression()
model.fit(
  train_data,
  [
      "col1",
      "col2",
      "col3",
  ],
  "Y",
  test_data,
)

Note

All the ML models that were introduced in version 1.0.x are also supported in version 1.1.x .

Performance

QueryProfiler has been greatly supplemented in this release:

QueryProfilerInterface

Now we have added the functionality of a session_control_param parameter. This allows users to enter the alter session SQL before profiling the queries.

QueryProfilerInterface

  • Added many more metrics for the profiled queries such as:

    • rows_filtered_sip

    • container_rows_filtered_sip

    • container_rows_pruned_sip

    and more…

  • There is a new tab which helps you select particular tooltips from any select path id.

  • A new tab also highlights if there are any non-default SESSION PARAMETERS .

  • Improved the efficiency of plotting the tree by chaching results.

QueryProfilerComparison

  • QueryProfilerComparison class offers an extended set of functionalities, enabling the creation of complex trees with multiple metrics.

from verticapy.performance.vertica import QueryProfilerInterface

qprof_interface_1 = QueryProfilerInterface(
  key_id = "key_1",
  target_schema = "schema_1",
)

qprof_interface_2 = QueryProfilerInterface(
  key_id = "key_2",
  target_schema = "schema_1",
)

from verticapy.performance.vertica import QueryProfilerComparison

qprof_compare = QueryProfilerComparison(qprof_interface_1, qprof_interface_2)

qprof_compare.get_qplan_tree()
_images/whats_new_1_1_0_qprof_get_qplan_tree.png

Deprecations

Warning

Because of the re-structuring of VerticaPy, some previous imports will not work.

Please look at the latest doc for the up-to-date imports.