Comments (2)
you could also return properties(n)
What is your use-case for returning the full node data?
We could add some code within the connector that turns nodes / relationships into constructs that Spark can work with, e.g maps or flattened objects, but that would require quite some magic which might be confusing for users.
So perhaps an error message that points out properties(n)
or even a map projection like: n { id: id(n), labels: labels(n), .* } as node
would make more sense?
from neo4j-spark-connector.
Also nodes in Neo4j can have different number (and types) of attributes, so flattening them out into columns automatically wouldn't work really well.
from neo4j-spark-connector.
Related Issues (20)
- Issue : When updating node data via the Spark Connector HOT 2
- java.lang.LinkageError - Spark 3.1.2 neo4j - 4.1.0_for_spark_3 HOT 1
- IllegalArgumentException: Please provide a valid READ query
- Write example should be completed
- Code examples to use both Scala and Python HOT 1
- Update Spark v5 documentation for Neo4j v5 HOT 2
- can't acquire ExclusiveLock HOT 3
- very slow writing of data HOT 3
- Upgrade Cypher DSL to the latest version that supports a JDK 8 baseline HOT 1
- spark version validation fails on EMR / EMR Serverless HOT 1
- Not able to Insert Neo4j Map Data type using the neo4j-spark connector
- First-class support to GDS
- Project build fails after SBT upgrade to 1.9.0, but works for 1.8.3 HOT 1
- Support for pushdown limit
- Add example notebooks
- Transaction Retries using pyspark HOT 1
- Problem with datetime properties with null values HOT 1
- 5.2.0 missing from maven? HOT 2
- Neo4j connector is currently unusable to write data from Databricks with Unity Catalog enabled HOT 2
- Streaming reads: offsets are not loaded from checkpoint when restarting a stream after failure. HOT 10
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