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Posted to github@arrow.apache.org by "Lordworms (via GitHub)" <gi...@apache.org> on 2024/02/12 01:55:30 UTC
[PR] feat: issue #9157 adding record_batches for Vec [arrow-datafusion]
Lordworms opened a new pull request, #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197
## Which issue does this PR close?
#9157
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Closes #.
## Rationale for this change
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1486271065
##########
datafusion/core/tests/dataframe/mod.rs:
##########
@@ -1431,6 +1432,89 @@ async fn unnest_analyze_metrics() -> Result<()> {
Ok(())
}
+#[tokio::test]
+async fn test_read_batches() -> Result<()> {
+ let config = SessionConfig::new();
+ let runtime = Arc::new(RuntimeEnv::default());
+ let state = SessionState::new_with_config_rt(config, runtime);
+ let ctx = SessionContext::new_with_state(state);
+
+ let schema = Arc::new(Schema::new(vec![
+ Field::new("id", DataType::Int32, false),
+ Field::new("number", DataType::Float32, false),
+ ]));
+
+ let batches = vec![
+ RecordBatch::try_new(
+ schema.clone(),
+ vec![
+ Arc::new(Int32Array::from(vec![1, 2, 3, 4, 5])),
+ Arc::new(Float32Array::from(vec![1.12, 3.40, 2.33, 9.10, 6.66])),
+ ],
+ )
+ .unwrap(),
+ RecordBatch::try_new(
+ schema.clone(),
+ vec![
+ Arc::new(Int32Array::from(vec![3, 4, 5])),
+ Arc::new(Float32Array::from(vec![1.11, 2.22, 3.33])),
+ ],
+ )
+ .unwrap(),
+ RecordBatch::try_new(
Review Comment:
Minor: I suggest making the test shorter by feeding in 2 batches rather than 5
##########
datafusion/core/src/execution/context/mod.rs:
##########
@@ -934,7 +934,26 @@ 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: SchemaRef = batches.peek().unwrap().schema().clone();
Review Comment:
Perhaps something like
```suggestion
let schema: SchemaRef = if let Some(schema) = batches.peek() {
schema.clone()
} else {
// use empty schema)
Arc::new(Schema::new())
};
```
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Re: [PR] feat: issue #9157 adding record_batches for Vec [arrow-datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1485730350
##########
datafusion/core/src/execution/context/mod.rs:
##########
@@ -934,7 +934,26 @@ 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: SchemaRef = batches.peek().unwrap().schema().clone();
Review Comment:
Is there any way we can avoid an unwrap here?
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey merged PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#issuecomment-1939242253
CI failure seems unrelated -- I retriggered it
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1488022541
##########
datafusion/core/src/execution/context/mod.rs:
##########
@@ -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:
TLDR is that it is added by https://docs.rs/datafusion/latest/datafusion/physical_optimizer/enforce_distribution/struct.EnforceDistribution.html -- the rules about when it happens are non trivial but basically are "when it helps"
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1487644594
##########
datafusion/core/src/execution/context/mod.rs:
##########
@@ -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:
There is a difference (as you say the code in this PR makes its own partition). I think you are right that a single partition might be better (and DataFusion will repartition the plan into multiple partitions) if necessary
Is this something you can do @Lordworms ? Otherwise we can merge this PR as is and make it as a follow on change.
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1486439247
##########
datafusion/core/tests/dataframe/mod.rs:
##########
@@ -1489,7 +1489,7 @@ async fn test_read_batches_empty() -> Result<()> {
let state = SessionState::new_with_config_rt(config, runtime);
let ctx = SessionContext::new_with_state(state);
- let schema = Arc::new(Schema::new(vec![
+ let _schema = Arc::new(Schema::new(vec![
Review Comment:
I think you could simply delete this statement entirely as the Schema is not needed
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey commented on PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#issuecomment-1943418426
Thanks for this :+1:
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "Lordworms (via GitHub)" <gi...@apache.org>.
Lordworms commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1486337434
##########
datafusion/core/src/execution/context/mod.rs:
##########
@@ -934,7 +934,26 @@ 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: SchemaRef = batches.peek().unwrap().schema().clone();
Review Comment:
Got it!
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "Lordworms (via GitHub)" <gi...@apache.org>.
Lordworms commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1486441900
##########
datafusion/core/tests/dataframe/mod.rs:
##########
@@ -1489,7 +1489,7 @@ async fn test_read_batches_empty() -> Result<()> {
let state = SessionState::new_with_config_rt(config, runtime);
let ctx = SessionContext::new_with_state(state);
- let schema = Arc::new(Schema::new(vec![
+ let _schema = Arc::new(Schema::new(vec![
Review Comment:
done
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "Jefffrey (via GitHub)" <gi...@apache.org>.
Jefffrey commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1487637459
##########
datafusion/core/src/execution/context/mod.rs:
##########
@@ -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:
Hmm, is there any difference to mapping each batch into its own vec (which seemingly represents a different partition?) vs just collecting the batches into a single vec and passing in a single vec?
e.g. something like
```suggestion
let provider =
MemTable::try_new(schema, vec![batches.collect()])?;
```
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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "Lordworms (via GitHub)" <gi...@apache.org>.
Lordworms commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1487903232
##########
datafusion/core/src/execution/context/mod.rs:
##########
@@ -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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Re: [PR] Add `SessionContext::record_batches` [arrow-datafusion]
Posted by "Lordworms (via GitHub)" <gi...@apache.org>.
Lordworms commented on code in PR #9197:
URL: https://github.com/apache/arrow-datafusion/pull/9197#discussion_r1488026849
##########
datafusion/core/src/execution/context/mod.rs:
##########
@@ -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:
Thanks, I would read about it and commit the changes soon.
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