Lordworms commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1487903232
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datafusion/core/src/execution/context/mod.rs:
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@@ -934,7 +935,30 @@ impl SessionContext {
.build()?,
))
}
-
+ /// Create a [`DataFrame`] for reading a [`Vec[`RecordBatch`]`]
+ pub fn read_batches(
+ &self,
+ batches: impl IntoIterator<Item = RecordBatch>,
+ ) -> Result<DataFrame> {
+ // check schema uniqueness
+ let mut batches = batches.into_iter().peekable();
+ let schema = if let Some(batch) = batches.peek() {
+ batch.schema().clone()
+ } else {
+ Arc::new(Schema::empty())
+ };
+ let provider =
+ MemTable::try_new(schema, batches.map(|batch|
vec![batch]).collect())?;
Review Comment:
sure, so what we need to do is to flatten all the batches into a vec? I
wonder in what situation the datafusion would do the repartition? Is there any
doc for this?
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