NVIDIA/cudf-spark
Spark RAPIDS plugin - accelerate Apache Spark with GPUs
What is NVIDIA/cudf-spark?
NVIDIA/cudf-spark is a repository whose own project materials describe it as Spark RAPIDS plugin - accelerate Apache Spark with GPUs NOTE: For the latest stable README.md ensure you are on the main branch. This Graphify demo keeps NVIDIA/cudf-spark as the primary keyword while adding source-derived context, README signals, and an interactive code graph for deeper exploration.
Source: README.md at d48f8f0d51f9
Graphify architecture insights for NVIDIA/cudf-spark
NVIDIA/cudf-spark has a large Graphify map with 37,581 nodes, 80,470 edges, and 1,761 communities. The graph turns NVIDIA/cudf-spark into an architecture map: dense communities point to related implementation areas, while high-degree nodes from the Graphify report are good starting points for code review, onboarding, and dependency exploration.
README-derived project notes
- NVIDIA/cudf-spark is described by its project source as: Spark RAPIDS plugin - accelerate Apache Spark with GPUs NOTE: For the latest stable README.md ensure you are on the main branch
- The project README exposes reader-facing sections such as Compatibility, Tuning, Configuration, and Issues Questions, which helps explain how NVIDIA/cudf-spark is positioned and used
- NVIDIA/cudf-spark was captured from the repository at commit d48f8f0d51f9 and analyzed in code-only mode, so this page connects project documentation with the generated code graph
- NVIDIA/cudf-spark is primarily a Scala project, which makes the graph useful for understanding important files, modules, and dependency relationships before opening the source tree
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Graphify report highlights
Summary
- 37581 nodes · 80470 edges · 1761 communities (1556 shown, 205 thin omitted)
- Extraction: 90% EXTRACTED · 10% INFERRED · 0% AMBIGUOUS · INFERRED: 8380 edges (avg confidence: 0.8)
- Token cost: 0 input · 0 output
God nodes
- assert_gpu_and_cpu_are_equal_collect() - 1272 edges
- RapidsConf - 577 edges
- unary_op_df() - 544 edges
- with_cpu_session() - 454 edges
- GpuMetric - 414 edges
- gen_df() - 397 edges
Surprising connections
- test_mod_pmod_long_min_value() --calls--> assert_gpu_and_cpu_are_equal_collect() [INFERRED]
- test_decimal_nullability_of_overflow_for_binary_ops() --calls--> assert_gpu_and_cpu_are_equal_collect() [INFERRED]
- test_array_transform_non_deterministic() --calls--> assert_gpu_and_cpu_are_equal_collect() [INFERRED]
- test_sql_array_scalars() --calls--> assert_gpu_and_cpu_are_equal_collect() [INFERRED]
FAQ about NVIDIA/cudf-spark
What is NVIDIA/cudf-spark?
NVIDIA/cudf-spark is described by its repository as Spark RAPIDS plugin - accelerate Apache Spark with GPUs NOTE: For the latest stable README.md ensure you are on the main branch. This page adds a Graphify code graph so readers can inspect how the project is structured.
What does the NVIDIA/cudf-spark Graphify graph show?
NVIDIA/cudf-spark has a large Graphify map with 37,581 nodes, 80,470 edges, and 1,761 communities. It highlights communities, important nodes, and relationships extracted from the captured source commit.
Why use Graphify to explore NVIDIA/cudf-spark?
Graphify gives NVIDIA/cudf-spark a visual architecture layer, making it easier to find central files, understand module boundaries, and decide where to start reading the code.
Where did the NVIDIA/cudf-spark page content come from?
The project notes are derived from README.md at d48f8f0d51f9, repository metadata, and the Graphify report generated for the captured commit.