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4 changes: 2 additions & 2 deletions tpchgen-arrow/Cargo.toml
Original file line number Diff line number Diff line change
Expand Up @@ -9,9 +9,9 @@ readme = "README.md"
license = "Apache-2.0"

[dependencies]
arrow = { version = "56", default-features = false, features = ["prettyprint"] }
arrow = { version = "57", default-features = false, features = ["prettyprint"] }
tpchgen = { path = "../tpchgen", version = "2.0.1" }

[dev-dependencies]
arrow-csv = "56"
arrow-csv = "57"
chrono = "0.4.39"
4 changes: 2 additions & 2 deletions tpchgen-cli/Cargo.toml
Original file line number Diff line number Diff line change
Expand Up @@ -10,8 +10,8 @@ license = { workspace = true }
repository = { workspace = true }

[dependencies]
arrow = "56"
parquet = "56"
arrow = "57"
parquet = "57"
clap = { version = "4.5.32", features = ["derive"] }
tpchgen = { path = "../tpchgen", version = "2.0.1"}
tpchgen-arrow = { path = "../tpchgen-arrow", version = "2.0.1" }
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10 changes: 8 additions & 2 deletions tpchgen-cli/src/parquet.rs
Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ use crate::statistics::WriteStatistics;
use arrow::datatypes::SchemaRef;
use futures::StreamExt;
use log::debug;
use parquet::arrow::arrow_writer::{compute_leaves, get_column_writers, ArrowColumnChunk};
use parquet::arrow::arrow_writer::{compute_leaves, ArrowColumnChunk};
use parquet::arrow::ArrowSchemaConverter;
use parquet::basic::Compression;
use parquet::file::properties::WriterProperties;
Expand Down Expand Up @@ -140,7 +140,13 @@ where
I: RecordBatchIterator,
{
// Create writers for each of the leaf columns
let mut col_writers = get_column_writers(&parquet_schema, &writer_properties, &schema).unwrap();
#[allow(deprecated)]
let mut col_writers = parquet::arrow::arrow_writer::get_column_writers(
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we just need to change this to follow the example here: https://docs.rs/parquet/latest/parquet/arrow/arrow_writer/struct.ArrowColumnWriter.html

&parquet_schema,
&writer_properties,
&schema,
)
.unwrap();

// generate the data and send it to the tasks (via the sender channels)
for batch in iter {
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