diff --git a/tpchgen-arrow/Cargo.toml b/tpchgen-arrow/Cargo.toml
index c7563b4..b40244c 100644
--- a/tpchgen-arrow/Cargo.toml
+++ b/tpchgen-arrow/Cargo.toml
@@ -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"
diff --git a/tpchgen-cli/Cargo.toml b/tpchgen-cli/Cargo.toml
index a6e9f6a..12dbe37 100644
--- a/tpchgen-cli/Cargo.toml
+++ b/tpchgen-cli/Cargo.toml
@@ -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" }
diff --git a/tpchgen-cli/src/parquet.rs b/tpchgen-cli/src/parquet.rs
index 767aff4..1eba0a0 100644
--- a/tpchgen-cli/src/parquet.rs
+++ b/tpchgen-cli/src/parquet.rs
@@ -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;
@@ -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(
+        &parquet_schema,
+        &writer_properties,
+        &schema,
+    )
+    .unwrap();
 
     // generate the data and send it to the tasks (via the sender channels)
     for batch in iter {