A Dataflow pipeline is a self-contained, directed acyclic graph (DAG) of data processing steps that executes as a single, isolated job. Each pipeline run, or instance, is independent and does not have a built-in mechanism to directly share in-memory data or state with other running pipeline instances. While multiple pipelines can read from or write to a common external storage system like a Pub/Sub topic or a BigQuery table, this is interaction via external sources and sinks, not direct data sharing between the pipeline execution instances themselves. The core processing logic and intermediate data within one pipeline job are isolated from another.

A. A pipeline is fundamentally a series of operations, called PTransforms, that are applied to distributed datasets, called PCollections. This statement is true.

B. A pipeline is the definition of a data processing task. When you execute a pipeline using the Dataflow service, it creates and runs a Dataflow job. This statement is true.

C. The structure of a pipeline, with its PCollections (nodes) and PTransforms (edges), forms a Directed Acyclic Graph (DAG) that represents the entire workflow. This statement is true.

1. Google Cloud Documentation, Dataflow, "Pipelines": "A pipeline is a graph of transformations that are applied to collections of data. In the Beam SDKs, a pipeline is represented by an object of the Pipeline class... When you run your pipeline, it executes as a single job on the Dataflow service." This source confirms that a pipeline is a graph of operations (A, C) that runs as a job (B). The concept of a job being a "single" execution implies isolation, contradicting D.

2. Apache Beam Programming Guide, "Overview": "A pipeline is a user-constructed graph of PTransforms that defines the data processing job... The Beam SDKs use this graph to create a Directed Acyclic Graph (DAG) of steps." This reference directly supports that a pipeline is a graph of steps (C) and represents a job (B).

3. Google Cloud Documentation, Dataflow, "Execution graph": "When you run your Dataflow pipeline, Dataflow creates an execution graph from the PTransforms and PCollections in your code. This execution graph is called a pipeline..." This source explicitly links the pipeline to a graph structure (C). The lack of any mention of inter-pipeline communication mechanisms further supports that D is not a feature.