FEAT-#7254: Support right merge/join

[local-dev-korbit-ai-mentor]

What do these changes do?

Blocked on modin-project/modin#7251

Performance: 1.7 sec (the PR) vs 3.1 sec (on main) on Ray (8 cores)

import modin.pandas as pd
from time import time
import numpy as np
from modin.utils import execute

np.random.seed(42)

df1 = pd.DataFrame(np.random.randint(0, 100_000,size=(400_000, 64)))
df2 = pd.DataFrame(np.random.randint(0, 100_000,size=(400_000, 64)))
execute(df1)
execute(df2)


for _ in range(3):
    start = time()
    result = pd.merge(df1, df2, how="right", on=1)
    execute(result)
    print(f"{result.shape=}")
    print(f"merge time: {time()-start}")

• first commit message and PR title follow format outlined here

  NOTE: If you edit the PR title to match this format, you need to add another commit (even if it's empty) or amend your last commit for the CI job that checks the PR title to pick up the new PR title.

• passes flake8 modin/ asv_bench/benchmarks scripts/doc_checker.py
• passes black --check modin/ asv_bench/benchmarks scripts/doc_checker.py
• signed commit with git commit -s
• Resolves #7254
• tests added and passing
• module layout described at docs/development/architecture.rst is up-to-date

Description by Korbit AI

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What change is being made?

Add support for right merge/join in the row_axis_merge function within modin/core/storage_formats/pandas/merge.py.

Why are these changes being made?

This change addresses the need for right merge/join functionality, which was previously unsupported. The implementation ensures that the merge operation correctly handles the right join by swapping the left and right DataFrames when necessary and adjusting the metadata computation accordingly.

[local-dev-korbit-ai-mentor]

Clone of the PR modin-project/modin#7226

[korbit-ai]

My review is in progress 📖 - I will have feedback for you in a few minutes!

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[korbit-ai]

I have reviewed your code and did not find any issues!

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[furwellness]

/review

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PR Reviewer Guide 🔍

⏱️ Estimated effort to review: 2 🔵🔵⚪⚪⚪

🧪 PR contains tests

🔒 No security concerns identified

⚡ Key issues to review Code Duplication The code for computing result metadata is duplicated with a slight variation. Consider refactoring to avoid repetition. Potential Performance Impact The condition for swapping left and right dataframes might affect performance in some cases. Consider adding a comment explaining the rationale behind this optimization.