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diff --git a/sqlx-sqlite/Cargo.toml b/sqlx-sqlite/Cargo.toml
new file mode 100644
index 0000000..a796f9a
--- /dev/null
+++ b/sqlx-sqlite/Cargo.toml
@@ -0,0 +1,22 @@
+[package]
+name = "sqlx-sqlite-index-example"
+version = "0.1.0"
+edition = "2021"
+
+[dependencies]
+anyhow = "~1"
+async-trait = "0"
+datafusion = { features = ["backtrace"], git = "https://github.com/apache/datafusion.git" }
+datafusion-expr = { git = "https://github.com/apache/datafusion.git" }
+datafusion-optimizer = { git = "https://github.com/apache/datafusion.git" }
+datafusion-common = { git = "https://github.com/apache/datafusion.git" }
+datafusion-physical-expr = { git = "https://github.com/apache/datafusion.git" }
+datafusion-sql = { git = "https://github.com/apache/datafusion.git" }
+sqlx = { version = "~0", features = [ "runtime-tokio", "sqlite" ] }
+tempfile = "3"
+thiserror = "1"
+tokio = { version = "1", features = [ "rt-multi-thread", "macros" ] }
+url = "2"
+object_store = { version = "0" }
+sea-query = { version = "0", features = ["backend-sqlite", "hashable-value", "derive", "thread-safe"] }
+sea-query-binder = { version = "0", features = ["sqlx-sqlite" ] }
diff --git a/sqlx-sqlite/README.md b/sqlx-sqlite/README.md
new file mode 100644
index 0000000..ebdc72d
--- /dev/null
+++ b/sqlx-sqlite/README.md
@@ -0,0 +1,73 @@
+# DataFusion secondary index example using SQLx
+
+This example demonstrates how to integrate a secondary index built using SQLite via SQLx with DataFusion.
+
+SQLite is used as a stand-in for an external remote relational database, it should be easy to adapt this example to use another database.
+
+This examples should be considered incomplete: it does not try to handle **many** edge cases or push down filters as much as possible.
+It is meant to sketch out the basic idea, not be a complete implementation.
+
+## Running the example
+
+To run the example you just need to have Rust and Cargo installed. Then you can run just `cargo run`.
+
+You'll see output like this:
+
+```text
+** Table Provider:
+IndexTableProvider
+---- Index ----
+SQLiteIndex()
+
+
+** Select data, no predicates:
++---------------+-------+
+| file_name     | value |
++---------------+-------+
+| file1.parquet | 0     |
+| file1.parquet | 1     |
+| file1.parquet | 2     |
+| file1.parquet | 3     |
+| file1.parquet | 4     |
+| file1.parquet | 5     |
+| file1.parquet | 6     |
+| file1.parquet | 7     |
+| file1.parquet | 8     |
+| file1.parquet | 9     |
++---------------+-------+
+Files scanned: [("file1.parquet", ParquetAccessPlan { row_groups: [Scan, Scan] }), ("file2.parquet", ParquetAccessPlan { row_groups: [Scan, Scan] }), ("file3.parquet", ParquetAccessPlan { row_groups: [Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan] })]
+
+** Select data, predicate `value = 150`
++---------------+-------+
+| file_name     | value |
++---------------+-------+
+| file2.parquet | 150   |
++---------------+-------+
+Files scanned: [("file2.parquet", ParquetAccessPlan { row_groups: [Skip, Scan] })]
+
+** Select data, predicate `value < 20 OR value > 500`
++---------------+--------------------------+
+| file_name     | COUNT(index_table.value) |
++---------------+--------------------------+
+| file1.parquet | 20                       |
+| file3.parquet | 2499                     |
++---------------+--------------------------+
+Files scanned: [("file1.parquet", ParquetAccessPlan { row_groups: [Scan, Skip] }), ("file3.parquet", ParquetAccessPlan { row_groups: [Skip, Skip, Skip, Skip, Skip, Skip, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan, Scan] })]
+
+** Select data, predicate `value < 20 AND text = 'a'`
++---------------+--------------------------+
+| file_name     | COUNT(index_table.value) |
++---------------+--------------------------+
+| file1.parquet | 1                        |
++---------------+--------------------------+
+Files scanned: [("file1.parquet", ParquetAccessPlan { row_groups: [Scan, Skip] })]
+
+** Select data, predicate `value > 500 AND text = 'a'`
++-----------+--------------------------+
+| file_name | COUNT(index_table.value) |
++-----------+--------------------------+
++-----------+--------------------------+
+Files scanned: []
+```
+
+As you can see the index is being used to select which row groups to read from the Parquet files.
diff --git a/sqlx-sqlite/index.db b/sqlx-sqlite/index.db
new file mode 100644
index 0000000..4ebf78c
Binary files /dev/null and b/sqlx-sqlite/index.db differ
diff --git a/sqlx-sqlite/src/conversions.rs b/sqlx-sqlite/src/conversions.rs
new file mode 100644
index 0000000..50351d3
--- /dev/null
+++ b/sqlx-sqlite/src/conversions.rs
@@ -0,0 +1,229 @@
+use datafusion::arrow::{array::{Array, ArrayRef, AsArray}, datatypes::DataType};
+use datafusion_common::ScalarValue;
+use datafusion_expr::Operator;
+use datafusion::arrow::datatypes;
+use datafusion_physical_expr::{expressions as phys_expr, PhysicalExprRef};
+use sea_query::{Alias, BinOper, CaseStatement, ColumnRef, IntoIden, SimpleExpr, Value};
+
+
+/// Convert a DataFusion PhysicalExpr to a SeaQuery SimpleExpr
+pub fn physical_expr_to_sea_query(expr: &PhysicalExprRef) -> SimpleExpr {
+    if let Some(expr) = expr.as_any().downcast_ref::<phys_expr::BinaryExpr>(){
+        let left = physical_expr_to_sea_query(expr.left());
+        let right = physical_expr_to_sea_query(expr.right());
+        match expr.op() {
+            Operator::Eq => left.binary(BinOper::Equal, right),
+            Operator::NotEq => left.binary(BinOper::NotEqual, right),
+            Operator::Lt => left.binary(BinOper::SmallerThan, right),
+            Operator::LtEq => left.binary(BinOper::SmallerThanOrEqual, right),
+            Operator::Gt => left.binary(BinOper::GreaterThan, right),
+            Operator::GtEq => left.binary(BinOper::GreaterThanOrEqual, right),
+            Operator::Plus => left.binary(BinOper::Add, right),
+            Operator::Minus => left.binary(BinOper::Sub, right),
+            Operator::Multiply => left.binary(BinOper::Mul, right),
+            Operator::Divide => left.binary(BinOper::Div, right),
+            Operator::Modulo => left.binary(BinOper::Mod, right),
+            Operator::And => left.binary(BinOper::And, right),
+            Operator::Or => left.binary(BinOper::Or, right),
+            Operator::LikeMatch => left.binary(BinOper::Like, right),
+            Operator::NotLikeMatch => left.binary(BinOper::NotLike, right),
+            Operator::BitwiseShiftLeft => left.binary(BinOper::LShift, right),
+            Operator::BitwiseShiftRight => left.binary(BinOper::RShift, right),
+            _ => SimpleExpr::Constant(Value::Bool(Some(true)))
+        }
+    } else if let Some(expr) = expr.as_any().downcast_ref::<phys_expr::Column>() {
+        SimpleExpr::Column(ColumnRef::Column(Alias::new(expr.name().to_string()).into_iden()))
+    } else if let Some(expr) = expr.as_any().downcast_ref::<phys_expr::Literal>() {
+        match expr.value() {
+            ScalarValue::Null => SimpleExpr::Keyword(sea_query::Keyword::Null),
+            ScalarValue::Boolean(v) => SimpleExpr::Constant(Value::Bool(*v)),
+            ScalarValue::Float32(v) => SimpleExpr::Constant(Value::Float(*v)),
+            ScalarValue::Float64(v) => SimpleExpr::Constant(Value::Double(*v)),
+            ScalarValue::Int8(v) => SimpleExpr::Constant(Value::TinyInt(*v)),
+            ScalarValue::Int16(v) => SimpleExpr::Constant(Value::SmallInt(*v)),
+            ScalarValue::Int32(v) => SimpleExpr::Constant(Value::Int(*v)),
+            ScalarValue::Int64(v) => SimpleExpr::Constant(Value::BigInt(*v)),
+            ScalarValue::UInt8(v) => SimpleExpr::Constant(Value::TinyUnsigned(*v)),
+            ScalarValue::UInt16(v) => SimpleExpr::Constant(Value::SmallUnsigned(*v)),
+            ScalarValue::UInt32(v) => SimpleExpr::Constant(Value::Unsigned(*v)),
+            ScalarValue::UInt64(v) => SimpleExpr::Constant(Value::BigUnsigned(*v)),
+            ScalarValue::Utf8(v) => match v {
+                Some(v) => SimpleExpr::Constant(Value::String(Some(Box::new(v.to_string())))),
+                None => SimpleExpr::Constant(Value::String(None)),
+            },
+            ScalarValue::LargeUtf8(v) => match v {
+                Some(v) => SimpleExpr::Constant(Value::String(Some(Box::new(v.to_string())))),
+                None => SimpleExpr::Constant(Value::String(None)),
+            },
+            ScalarValue::Binary(v) => match v {
+                Some(v) => SimpleExpr::Constant(Value::Bytes(Some(Box::new(v.to_vec())))),
+                None => SimpleExpr::Constant(Value::Bytes(None)),
+            },
+            ScalarValue::FixedSizeBinary(_, v) => match v {
+                Some(v) => SimpleExpr::Constant(Value::Bytes(Some(Box::new(v.to_vec())))),
+                None => SimpleExpr::Constant(Value::Bytes(None)),
+            },
+            ScalarValue::LargeBinary(v) => match v {
+                Some(v) => SimpleExpr::Constant(Value::Bytes(Some(Box::new(v.to_vec())))),
+                None => SimpleExpr::Constant(Value::Bytes(None)),
+            },
+            // Extend with other types, e.g. to support arrays, dates, etc.
+            _ => SimpleExpr::Constant(Value::Bool(Some(true)))
+        }
+    } else if let Some(expr) = expr.as_any().downcast_ref::<phys_expr::CaseExpr>() {
+        let mut case = CaseStatement::new();
+        for (when, then) in expr.when_then_expr() {
+            case = case.case(physical_expr_to_sea_query(when), physical_expr_to_sea_query(then));
+        }
+        if let Some(else_exp) = expr.else_expr() {
+            case = case.finally(physical_expr_to_sea_query(else_exp));
+        };
+        SimpleExpr::Case(Box::new(case))
+    } else {
+        SimpleExpr::Constant(Value::Bool(Some(true)))
+    }
+}
+
+/// Convert a DataFusion Array to a Vec of SeaQuery Values
+pub fn array_to_values(array: ArrayRef) -> Option<Vec<Value>> {
+    let values = match array.data_type() {
+        DataType::Int8 => {
+            let array = array.as_primitive::<datatypes::Int8Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::TinyInt(Some(v)),
+                    None => Value::TinyInt(None)
+                }
+            }).collect()
+        }
+        DataType::Int16 => {
+            let array = array.as_primitive::<datatypes::Int16Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::SmallInt(Some(v)),
+                    None => Value::SmallInt(None)
+                }
+            }).collect()
+        }
+        DataType::Int32 => {
+            let array = array.as_primitive::<datatypes::Int32Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::Int(Some(v)),
+                    None => Value::Int(None)
+                }
+            }).collect()
+        }
+        DataType::Int64 => {
+            let array = array.as_primitive::<datatypes::Int64Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::BigInt(Some(v)),
+                    None => Value::BigInt(None)
+                }
+            }).collect()
+        }
+        DataType::UInt8 => {
+            let array = array.as_primitive::<datatypes::UInt8Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::TinyUnsigned(Some(v)),
+                    None => Value::TinyUnsigned(None)
+                }
+            }).collect()
+        }
+        DataType::UInt16 => {
+            let array = array.as_primitive::<datatypes::UInt16Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::SmallUnsigned(Some(v)),
+                    None => Value::SmallUnsigned(None)
+                }
+            }).collect()
+        }
+        DataType::UInt32 => {
+            let array = array.as_primitive::<datatypes::UInt32Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::Unsigned(Some(v)),
+                    None => Value::Unsigned(None)
+                }
+            }).collect()
+        }
+        DataType::UInt64 => {
+            let array = array.as_primitive::<datatypes::UInt64Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::BigUnsigned(Some(v)),
+                    None => Value::BigUnsigned(None)
+                }
+            }).collect()
+        }
+        DataType::Float32 => {
+            let array = array.as_primitive::<datatypes::Float32Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::Float(Some(v)),
+                    None => Value::Float(None)
+                }
+            }).collect()
+        }
+        DataType::Float64 => {
+            let array = array.as_primitive::<datatypes::Float64Type>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::Double(Some(v)),
+                    None => Value::Double(None)
+                }
+            }).collect()
+        }
+        DataType::Utf8 => {
+            let array = array.as_string::<i32>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::String(Some(Box::new(v.to_string()))),
+                    None => Value::String(None)
+                }
+            }).collect()
+        }
+        DataType::LargeUtf8 => {
+            let array = array.as_string::<i64>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::String(Some(Box::new(v.to_string()))),
+                    None => Value::String(None)
+                }
+            }).collect()
+        }
+        DataType::Binary => {
+            let array = array.as_binary::<i32>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::Bytes(Some(Box::new(v.to_vec()))),
+                    None => Value::Bytes(None)
+                }
+            }).collect()
+        }
+        DataType::FixedSizeBinary(_) => {
+            let array = array.as_fixed_size_binary();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::Bytes(Some(Box::new(v.to_vec()))),
+                    None => Value::Bytes(None)
+                }
+            }).collect()
+        }
+        DataType::LargeBinary => {
+            let array = array.as_binary::<i64>();
+            array.iter().map(|v| {
+                match v {
+                    Some(v) => Value::Bytes(Some(Box::new(v.to_vec()))),
+                    None => Value::Bytes(None)
+                }
+            }).collect()
+        }
+        // Extend with other types, e.g. to support arrays, dates, etc.
+        _ => return None,
+    };
+    Some(values)
+}
\ No newline at end of file
diff --git a/sqlx-sqlite/src/index.rs b/sqlx-sqlite/src/index.rs
new file mode 100644
index 0000000..aa62456
--- /dev/null
+++ b/sqlx-sqlite/src/index.rs
@@ -0,0 +1,462 @@
+use std::{collections::HashMap, fmt::Display, fs::File, path::Path, sync::Arc};
+
+use datafusion::arrow::array::AsArray;
+use datafusion::arrow::datatypes::{DataType, SchemaRef, UInt64Type};
+use datafusion::physical_optimizer::pruning::PruningPredicate;
+use datafusion::{
+    datasource::physical_plan::parquet::{ParquetAccessPlan, RowGroupAccess, StatisticsConverter},
+    parquet::arrow::arrow_reader::ParquetRecordBatchReaderBuilder,
+};
+use datafusion_common::tree_node::TreeNode;
+use datafusion_common::{internal_datafusion_err, DataFusionError, Result, tree_node::{Transformed, TransformedResult}};
+use datafusion_physical_expr::PhysicalExpr;
+use sea_query::{
+    Alias, ColumnDef, CommonTableExpression, Expr as SeaQExpr, ForeignKey, ForeignKeyAction, Index, OnConflict, Query, SimpleExpr, SqliteQueryBuilder, Table, Value, WithClause
+};
+use sea_query_binder::SqlxBinder;
+use sqlx::SqlitePool;
+use datafusion_physical_expr::expressions as phys_expr;
+
+use crate::conversions::{array_to_values, physical_expr_to_sea_query};
+
+/// SQLite secondary index for a set of parquet files
+///
+/// It stores file-level data (filename and file size) as well as statistics for each column
+/// in each row group of each file.
+///
+/// When we scan a table we push down filters to the index to get a list of row groups that match
+/// and hence the files that need to be read.
+///
+/// It is possible for the index to store finer grained statistics or a complete row oriented index
+/// that filters down to individual rows within row groups.
+/// For example, if you have a table with an `id` column and you want to enable fast point lookups
+/// you could store the entire `id` column in the secondary index as a key/value map from `id` to
+/// (file_name, row_group, row_number) and use that to enable fast point lookups on parquet files.
+/// This is not implemented in this example.
+///
+/// The index is implemented as a SQLite database with two tables:
+/// - `file_statistics` with columns `file_id`, `file_name`, `file_size_bytes`, `row_group_count`, `row_count`
+/// - `row_group_statistics` with columns `file_id`, `row_group`, `row_count`,
+///    and min/max values for each column that is indexed.
+///
+/// Here is roughly what `SELECT * FROM file_statistics` would look like:
+/// | file_id | file_name     | file_size_bytes | row_group_count | row_count |
+/// | 1       | file1.parquet | 1234            | 3               | 1000      |
+///
+/// And `SELECT * FROM row_group_statistics`:
+/// | file_id | row_group | row_count | column1_null_count | column1_min | column1_max | column2_null_count | column2_min | column2_max |
+/// | 1       | 0         | 100       | 0                  | 1           | 100         | 0                  | "a"         | "z"         |
+/// | 1       | 1         | 100       | 0                  | 101         | 200         | 0                  | "a"         | "z"         |
+/// | 1       | 2         | 100       | 0                  | 201         | 300         | 0                  | "a"         | "z"         |
+/// | 2       | 0         | 50        | 0                  | 1           | 100         | 0                  | "x"         | "x"         |
+/// | 2       | 1         | 100       | 0                  | 101         | 200         | 0                  | "y"         | "z"         |
+/// | 2       | 2         | 150       | 0                  | 201         | 300         | 0                  | "123"       | "456"       |
+///
+/// To do filtering we rewrite the filter expression to a set of SQL expressions that can be evaluated against the index.
+/// For example, if we have a filter `a = 5` we would rewrite that to `a_min <= 5 AND a_max >= 5`:
+/// 
+/// ```sql
+/// WITH row_groups AS (
+///   SELECT file_id, row_group
+///   FROM row_group_statistics
+///   WHERE a_min <= 5 AND a_max >= 5
+/// )
+/// SELECT file_name, file_size_bytes, row_group
+/// FROM file_statistics
+/// JOIN row_groups USING (file_id)
+/// ```
+///
+/// While we use SQLite in this example, the index could be implemented with other databases or system.
+/// SQLite is just a convenient example that is also very similar to other RDBMS systems that you might use.
+#[derive(Debug)]
+pub struct SQLiteIndex {
+    pool: SqlitePool,
+    /// The index for the schema. Not all columns in the table need to be indexed.
+    schema: SchemaRef,
+}
+
+impl Display for SQLiteIndex {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        writeln!(f, "SQLiteIndex()")?;
+        Ok(())
+    }
+}
+
+impl SQLiteIndex {
+    pub async fn try_new(pool: SqlitePool, schema: SchemaRef) -> anyhow::Result<Self> {
+        let r = Self { pool, schema };
+        r.initialize().await?;
+        Ok(r)
+    }
+
+    /// Return the filenames / row groups that match the filter
+    ///
+    /// This function pushes down the filter to the index to get a list of row groups that match
+    /// and hence the files that need to be read.
+    ///
+    /// The filter is pushed down to the index by converting it to a set of SQL expressions
+    /// that can be evaluated by the index.
+    ///
+    /// The return value is a list of `(file_name, FileScanPlan)` tuples where `FileScanPlan` contains
+    /// the file metadata and the row groups that need to be scanned.
+    pub async fn get_files(
+        &self,
+        filter: Arc<dyn PhysicalExpr>,
+        schema: SchemaRef,
+    ) -> Result<Vec<(String, FileScanPlan)>> {
+        // Convert the predicate to a pruning predicate
+        // This transforms e.g. `a = 5` to `a_min <= 5 AND a_max >= 5`
+        let pruning = PruningPredicate::try_new(filter, schema.clone())?;
+        let predicate = pruning.predicate_expr().clone();
+        // PruningPredicate references the row count of each column as `{col}_row_count`
+        // But we don't store per-column row counts in the index, we store them a single time for the row group
+        // since the row count is the same for all columns in a row group.
+        // Thus we replace any references to `{col}_row_count` with `row_count` in the predicate.
+        let predicate = predicate.transform(|expr| {
+            if let Some(column) = expr.as_any().downcast_ref::<phys_expr::Column>() {
+                if column.name().ends_with("_row_count") {
+                    let column = phys_expr::Column::new(column.name().trim_end_matches("_row_count"), column.index());
+                    return Ok(Transformed::yes(Arc::new(column)));
+                }
+            }
+            Ok(Transformed::no(expr))
+        }).data()?;
+        // Convert a DataFusion PhysicalExpr to a SeaQuery SimpleExpr
+        let predicate = physical_expr_to_sea_query(&predicate);
+
+        let stats_query = Query::select()
+            .from(Alias::new("row_group_statistics"))
+            .columns(vec![
+                Alias::new("file_id"),
+                Alias::new("row_group"),
+            ])
+            .and_where(predicate).to_owned();
+        
+        let cte = CommonTableExpression::new()
+            .query(stats_query)
+            .table_name(Alias::new("row_groups")).to_owned();
+
+        let files_query = Query::select()
+            .from(Alias::new("file_statistics"))
+            .columns(vec![
+                Alias::new("file_name"),
+                Alias::new("file_size_bytes"),
+                Alias::new("row_group_count"),
+            ])
+            .inner_join(
+                Alias::new("row_groups"), 
+                SeaQExpr::col((Alias::new("file_statistics"), Alias::new("file_id"))).equals((Alias::new("row_groups"), Alias::new("file_id"))),
+            )
+            .column(Alias::new("row_group"))
+            .distinct()
+            .to_owned();
+
+        let query = files_query.with(WithClause::new().cte(cte).to_owned());
+
+        let (sql, values) = query.build_sqlx(SqliteQueryBuilder);
+
+        let row_groups: Vec<RowGroupToScan> = sqlx::query_as_with(&sql, values)
+            .fetch_all(&self.pool)
+            .await
+            .unwrap(); // TODO: handle error, possibly failing gracefully by scanning all files?
+
+        let mut file_scans: HashMap<String, FileScanPlan> = HashMap::new(); // file_name -> (file_size, row_groups)
+
+        for row_group in row_groups {
+            let file_scan_plan = file_scans.entry(row_group.file_name.clone()).or_insert(
+                FileScanPlan {
+                    file_size: row_group.file_size_bytes as u64,
+                    access_plan: ParquetAccessPlan::new_none(row_group.row_group_count as usize),
+                }
+            );
+            file_scan_plan.access_plan.set(row_group.row_group as usize, RowGroupAccess::Scan);
+        }
+
+        Ok(file_scans.into_iter().map(|(file_name, file_scan_plan)| (file_name, file_scan_plan)).collect())
+    }
+
+    /// Add a new file to the index
+    pub async fn add_file(&mut self, file: &Path) -> anyhow::Result<()> {
+        let file_name = file
+            .file_name()
+            .ok_or_else(|| internal_datafusion_err!("No filename"))?
+            .to_str()
+            .ok_or_else(|| internal_datafusion_err!("Invalid filename"))?;
+        let file_size = file.metadata()?.len();
+
+        let file = File::open(file).map_err(|e| {
+            DataFusionError::from(e).context(format!("Error opening file {file:?}"))
+        })?;
+
+        let reader = ParquetRecordBatchReaderBuilder::try_new(file)?;
+
+        // extract the parquet statistics from the file's footer
+        let metadata = reader.metadata();
+        let schema = reader.schema();
+        let parquet_schema = reader.parquet_schema();
+        let row_groups = metadata.row_groups();
+        let row_counts = StatisticsConverter::row_group_row_counts(row_groups.iter())?;
+        let mut row_group_statistics: Vec<_> = row_counts
+            .iter()
+            .enumerate()
+            .map(|(row_group, row_count)| {
+                RowGroupStatisticsInsert::new(row_group as i64, row_count.unwrap() as i64)
+            })
+            .collect();
+
+        for field in self.schema.fields() {
+            let column_name = field.name().clone();
+            let converter = StatisticsConverter::try_new(&column_name, schema, parquet_schema)?;
+            let null_counts = converter.row_group_null_counts(row_groups.iter())?;
+            let null_counts = null_counts.as_primitive::<UInt64Type>();
+
+            let (min_values, max_values) = match (array_to_values(converter.row_group_mins(row_groups.iter())?), array_to_values(converter.row_group_maxes(row_groups.iter())?)) {
+                (Some(min_values), Some(max_values)) => (min_values, max_values),
+                // If we don't support the type skip collecting statistics for this column
+                _ => continue,
+            };
+
+            for row_group in 0..metadata.num_row_groups() {
+                let statistics = ColumnStatistics {
+                    null_count: null_counts.value(row_group) as i64,
+                    min_max: (
+                        min_values[row_group].clone(),
+                        max_values[row_group].clone(),
+                    ),
+                };
+                row_group_statistics[row_group].column_statistics.push(statistics);
+            }
+        }
+
+        let file_statistics = FileStatisticsInsert {
+            file_name: file_name.to_string(),
+            file_size_bytes: file_size as i64,
+            row_group_count: metadata.num_row_groups() as i64,
+            row_count: metadata.file_metadata().num_rows(),
+        };
+
+        self.add_row(file_statistics, row_group_statistics).await?;
+        Ok(())
+    }
+
+    async fn add_row(
+        &self,
+        file_statistics: FileStatisticsInsert,
+        row_group_statistics: Vec<RowGroupStatisticsInsert>,
+    ) -> anyhow::Result<()> {
+        let mut transaction = self.pool.begin().await?;
+
+        let (sql, values) = Query::insert()
+            .into_table(Alias::new("file_statistics"))
+            .columns(vec![
+                Alias::new("file_name"),
+                Alias::new("file_size_bytes"),
+                Alias::new("row_group_count"),
+                Alias::new("row_count"),
+            ])
+            .values_panic(vec![
+                file_statistics.file_name.into(),
+                file_statistics.file_size_bytes.into(),
+                file_statistics.row_group_count.into(),
+                file_statistics.row_count.into(),
+            ])
+            .on_conflict(
+                OnConflict::columns(vec![Alias::new("file_name")])
+                    .update_columns(vec![
+                        Alias::new("file_size_bytes"),
+                        Alias::new("row_group_count"),
+                        Alias::new("row_count"),
+                    ])
+                    .to_owned(),
+            )
+            .returning(Query::returning().column(Alias::new("file_id")))
+            .build_sqlx(SqliteQueryBuilder);
+        let (file_id,): (i64,) = sqlx::query_as_with(&sql, values)
+            .fetch_one(&mut *transaction)
+            .await?;
+
+        // Delete any existing column statistics for this file
+        let (sql, values) = Query::delete()
+            .from_table(Alias::new("row_group_statistics"))
+            .and_where(SeaQExpr::col(Alias::new("file_id")).eq(file_id))
+            .build_sqlx(SqliteQueryBuilder);
+        sqlx::query_with(&sql, values)
+            .execute(&mut *transaction)
+            .await?;
+
+        let mut columns = vec![
+            Alias::new("file_id"),
+            Alias::new("row_group"),
+            Alias::new("row_count"),
+        ];
+
+        for field in self.schema.fields() {
+            columns.push(Alias::new(format!("{}_null_count", field.name())));
+            columns.push(Alias::new(format!("{}_min", field.name())));
+            columns.push(Alias::new(format!("{}_max", field.name())));
+        }
+
+        let mut query = Query::insert()
+            .into_table(Alias::new("row_group_statistics"))
+            .columns(columns)
+            .to_owned();
+
+        for statistics in row_group_statistics {
+            let mut values: Vec<SimpleExpr> = vec![
+                file_id.into(),
+                statistics.row_group.into(),
+                statistics.row_count.into(),
+            ];
+            for stats in statistics.column_statistics {
+                let (min, max) = stats.min_max;
+                values.push(stats.null_count.into());
+                values.push(min.into());
+                values.push(max.into());
+            }
+
+            query = query.values_panic(values).to_owned();
+        }
+
+        let (sql, values) = query.build_sqlx(SqliteQueryBuilder);
+
+        sqlx::query_with(&sql, values)
+            .execute(&mut *transaction)
+            .await?;
+
+        transaction.commit().await?;
+
+        Ok(())
+    }
+
+    /// Simple migration function that idempotently creates the table for the index
+    async fn initialize(&self) -> anyhow::Result<()> {
+        let query = r#"
+            CREATE TABLE IF NOT EXISTS file_statistics (
+                file_id INTEGER PRIMARY KEY AUTOINCREMENT,
+                file_name TEXT NOT NULL UNIQUE,
+                file_size_bytes INTEGER NOT NULL,
+                row_group_count INTEGER NOT NULL,
+                row_count INTEGER NOT NULL
+            )
+        "#;
+        sqlx::query(&query).execute(&self.pool).await?;
+
+        let sql = Table::create()
+            .table(Alias::new("file_statistics"))
+            .if_not_exists()
+            .col(ColumnDef::new(Alias::new("file_id")).integer().primary_key().auto_increment())
+            .col(ColumnDef::new(Alias::new("file_name")).string().not_null().unique_key())
+            .col(ColumnDef::new(Alias::new("file_size_bytes")).integer().not_null())
+            .col(ColumnDef::new(Alias::new("row_group_count")).integer().not_null())
+            .col(ColumnDef::new(Alias::new("row_count")).integer().not_null())
+            .to_owned()
+            .build(SqliteQueryBuilder);
+
+        sqlx::query(&sql).execute(&self.pool).await?;
+
+        let mut table = Table::create()
+            .table(Alias::new("row_group_statistics"))
+            .if_not_exists()
+            .col(ColumnDef::new(Alias::new("file_id")).integer().not_null())
+            .col(ColumnDef::new(Alias::new("row_group")).integer().not_null())
+            .col(ColumnDef::new(Alias::new("row_count")).integer().not_null())
+            .primary_key(Index::create().col(Alias::new("file_id")).col(Alias::new("row_group")))
+            .foreign_key(
+                ForeignKey::create()
+                    .from(Alias::new("row_group_statistics"), Alias::new("file_id"))
+                    .to(Alias::new("file_statistics"), Alias::new("file_id"))
+                    .on_delete(ForeignKeyAction::Cascade)
+            )
+            .to_owned();
+
+        for field in self.schema.fields().iter() {
+            table.col(
+                ColumnDef::new(Alias::new(format!("{}_null_count", field.name())))
+                .integer()
+                .not_null()
+            );
+            for suffix in ["min", "max"] {
+                let mut stats_col = ColumnDef::new(Alias::new(format!("{}_{}", field.name(), suffix)));
+                set_column_type(&mut stats_col, field.data_type().clone());
+                if !field.is_nullable() {
+                    stats_col.not_null();
+                }
+                table.col(&mut stats_col);
+            }
+        }
+
+        let sql = table.build(SqliteQueryBuilder);
+
+        sqlx::query(&sql).execute(&self.pool).await?;
+
+        Ok(())
+    }
+}
+
+fn set_column_type(column: &mut ColumnDef, field_type: DataType) -> &mut ColumnDef {
+    match field_type {
+        DataType::Int8 => column.tiny_integer(),
+        DataType::UInt8 => column.tiny_unsigned(),
+        DataType::Int16 => column.small_integer(),
+        DataType::UInt16 => column.small_unsigned(),
+        DataType::Int32 => column.integer(),
+        DataType::UInt32 => column.unsigned(),
+        DataType::Int64 => column.big_integer(),
+        DataType::UInt64 => column.big_unsigned(),
+        DataType::Float32 => column.float(),
+        DataType::Float64 => column.double(),
+        DataType::Utf8 => column.string(),
+        DataType::LargeUtf8 => column.string(),
+        DataType::Binary => column.binary(),
+        DataType::FixedSizeBinary(_) => column.binary(),
+        DataType::LargeBinary => column.binary(),
+        _ => todo!("Add support for more types"),
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct FileScanPlan {
+    pub file_size: u64,
+    pub access_plan: ParquetAccessPlan,
+}
+
+
+#[derive(Debug, Clone)]
+pub struct RowGroupStatisticsInsert {
+    pub row_group: i64,
+    pub row_count: i64,
+    /// Per-column statistics
+    pub column_statistics: Vec<ColumnStatistics>,
+}
+
+impl RowGroupStatisticsInsert {
+    pub fn new(row_group: i64, row_count: i64) -> Self {
+        Self {
+            row_group,
+            row_count,
+            column_statistics: vec![],
+        }
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct ColumnStatistics {
+    null_count: i64,
+    min_max: (Value, Value),
+}
+
+#[derive(Debug, Clone)]
+struct FileStatisticsInsert {
+    file_name: String,
+    file_size_bytes: i64,
+    row_group_count: i64,
+    row_count: i64,
+}
+
+#[derive(Debug, Clone, sqlx::FromRow)]
+pub struct RowGroupToScan {
+    pub file_name: String,
+    pub file_size_bytes: i64,
+    pub row_group_count: i64,
+    pub row_group: i64,
+}
diff --git a/sqlx-sqlite/src/main.rs b/sqlx-sqlite/src/main.rs
new file mode 100644
index 0000000..14be089
--- /dev/null
+++ b/sqlx-sqlite/src/main.rs
@@ -0,0 +1,445 @@
+use std::{
+    any::Any, cell::RefCell, fmt::Display, fs::{self, DirEntry, File}, ops::Range, path::{Path, PathBuf}, sync::{Arc, Mutex}
+};
+
+use datafusion::arrow::{array::{ArrayRef, Int32Array, RecordBatch, StringArray}, datatypes::{DataType, Field, Schema}};
+use datafusion::arrow::datatypes::SchemaRef;
+use async_trait::async_trait;
+use datafusion::{
+    datasource::{
+        listing::PartitionedFile,
+        physical_plan::{parquet::ParquetAccessPlan, FileScanConfig, ParquetExec},
+        TableProvider,
+    },
+    execution::{context::SessionState, object_store::ObjectStoreUrl},
+    parquet::{arrow::{arrow_reader::ParquetRecordBatchReaderBuilder, ArrowWriter}, file::properties::WriterProperties},
+    physical_plan::ExecutionPlan,
+    prelude::*,
+};
+use datafusion_common::{internal_datafusion_err, DFSchema, DataFusionError, Result};
+use datafusion_expr::{utils::conjunction, TableProviderFilterPushDown, TableType};
+use sqlx::SqlitePool;
+use tempfile::TempDir;
+use url::Url;
+
+use crate::index::SQLiteIndex;
+
+mod index;
+mod conversions;
+
+/// This example demonstrates building a secondary index over multiple Parquet
+/// files and using that index during query to skip ("prune") files and row groups
+/// that do not contain relevant data.
+///
+/// This example rules out irrelevant data using min/max values of a column
+/// extracted from the Parquet metadata. In a real system, the index could be
+/// more sophisticated, e.g. using inverted indices, bloom filters or other
+/// techniques.
+///
+/// Note this is a low level example for people who want to build their own
+/// custom indexes. To read a directory of parquet files as a table, you can use
+/// a higher level API such as [`SessionContext::read_parquet`] or
+/// [`ListingTable`], which also do file pruning based on parquet statistics
+/// (using the same underlying APIs)
+///
+/// # Diagram
+///
+/// ```text
+///                                   ┏━━━━━━━━━━━━━━━━━━━━━━━━┓
+///                                   ┃     Index              ┃
+///                                   ┃                        ┃
+///  step 1: predicate is   ┌ ─ ─ ─ ─▶┃ (sometimes referred to ┃
+///  evaluated against                ┃ as a "catalog" or      ┃
+///  data in the index      │         ┃ "metastore")           ┃
+///                                   ┗━━━━━━━━━━━━━━━━━━━━━━━━┛
+///                         │                      │
+///
+///                         │                      │
+/// ┌──────────────┐
+/// │  value = 150 │─ ─ ─ ─ ┘                      │
+/// └──────────────┘                                   ┌─────────────┐
+///  Predicate from query                          │   │             │
+///                                                    │  skip file  │
+///                                                │   │             │
+///                                                    └─────────────┘
+///                                                │   ┌─────────────┐
+///                   step 2: Index returns only       │  ┌────────┐ │
+///                   parquet files that might     │   │  │ scan   │ │
+///                   have matching data.              │  │ rg 0   │ │
+///                                                │   │  └────────┘ │
+///                                                    │  ┌────────┐ │
+///                                                │   │  │ skip   │ │
+///                                                ─ ▶ │  │ rg 3   │ │
+///                   The index can choose to          │  └────────┘ │
+///                   scan entire files,               │     ...     │
+///                   only some row-groups within      │  ┌────────┐ │
+///                   each file, or even               │  │  scan  │ │
+///                   individual rows within each      │  │  rg n  │ │
+///                   row group (not shown in this)    │  └────────┘ │
+///                   example                          └─────────────┘
+///                                                          ...
+///                                                    ┌─────────────┐
+///                                                    │             │
+///                                                    └─────────────┘
+///                                                     Parquet Files
+/// ```
+///
+#[tokio::main]
+async fn main() -> anyhow::Result<()> {
+    // We use an in-memory SQLite database to store the index for this example
+    // But the index could be stored in any database that SQLx supports, including a remote Postgres database
+    let pool = SqlitePool::connect("sqlite:index.db").await?;
+
+    // Demo data has three files, each with schema
+    // * file_name (string)
+    // * value (int32)
+    //
+    // The files are as follows:
+    // * file1.parquet (value: 0..100)
+    // * file2.parquet (value: 100..200)
+    // * file3.parquet (value: 200..3000)
+    let data = DemoData::try_new()?;
+
+    // Create a table provider with and  our special index.
+    let index = SQLiteIndex::try_new(
+        pool.clone(),
+        // You probably don't want to index _every_ column in your data
+        // For example, indexing a column of random strings like a UUID would be pointless
+        // using a min/max based index like this.
+        // In this example we choose to index only the "value" and "text" columns, ignoring "file_name"
+        Arc::new(
+            Schema::new(
+                vec![
+                    Field::new("value", DataType::Int32, false),
+                    Field::new("text", DataType::Utf8, false),
+                ]
+            )
+        )
+    ).await?;
+    let provider = Arc::new(IndexTableProvider::try_new(data.path(), index).await?);
+    println!("** Table Provider:");
+    println!("{provider}\n");
+
+    // Create a SessionContext for running queries that has the table provider
+    // registered as "index_table"
+    let ctx = SessionContext::new();
+    ctx.register_table("index_table", Arc::clone(&provider) as _)?;
+
+    // register object store provider for urls like `file://` work
+    let url = Url::try_from("file://").unwrap();
+    let object_store = object_store::local::LocalFileSystem::new();
+    ctx.register_object_store(&url, Arc::new(object_store));
+
+    // Select data from the table without any predicates (and thus no pruning)
+    println!("** Select data, no predicates:");
+    ctx.sql("SELECT file_name, value FROM index_table LIMIT 10")
+        .await?
+        .show()
+        .await?;
+    println!("Files scanned: {:?}\n", provider.last_execution());
+
+    // Run a query that uses the index to prune files.
+    //
+    // Using the predicate "value = 150", the IndexTable can skip reading file 1
+    // (max value 100) and file 3 (min value of 200)
+    println!("** Select data, predicate `value = 150`");
+    ctx.sql("SELECT file_name, value FROM index_table WHERE value = 150")
+        .await?
+        .show()
+        .await?;
+    println!("Files scanned: {:?}\n", provider.last_execution());
+
+    // likewise, we can use a more complicated predicate like
+    // "value < 20 OR value > 500" to read only file 1 and file 3
+    println!("** Select data, predicate `value < 20 OR value > 500`");
+    ctx.sql(
+        "SELECT file_name, count(value) FROM index_table \
+            WHERE value < 20 OR value > 500 GROUP BY file_name",
+    )
+    .await?
+    .show()
+    .await?;
+    println!("Files scanned: {:?}\n", provider.last_execution());
+
+
+    // it's also possible to combine predicates on multiple columns
+    // for example `value < 20 AND text = 'a'` would only read file 1
+    // while `value > 500 AND text = 'a'` would read no files
+    println!("** Select data, predicate `value < 20 AND text = 'a'`");
+    ctx.sql(
+        "SELECT file_name, count(value) FROM index_table \
+            WHERE value < 20 AND text = 'a' GROUP BY file_name",
+    )
+    .await?
+    .show()
+    .await?;
+    println!("Files scanned: {:?}\n", provider.last_execution());
+
+    println!("** Select data, predicate `value > 500 AND text = 'a'`");
+    ctx.sql(
+        "SELECT file_name, count(value) FROM index_table \
+            WHERE value > 500 AND text = 'a' GROUP BY file_name",
+    )
+    .await?
+    .show()
+    .await?;
+    println!("Files scanned: {:?}\n", provider.last_execution());
+
+    pool.close().await;
+
+    Ok(())
+}
+
+/// DataFusion `TableProvider` that uses [`IndexTableProvider`], a secondary
+/// index to decide which Parquet files and row groups to read.
+#[derive(Debug)]
+pub struct IndexTableProvider {
+    /// The index of the parquet files in the directory
+    index: SQLiteIndex,
+    /// the directory in which the files are stored
+    dir: PathBuf,
+    /// The schema of the table
+    schema: SchemaRef,
+    /// A simple log of the last execution
+    last_execution: Mutex<RefCell<SimpleExecutionLog>>
+}
+
+impl Display for IndexTableProvider {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        writeln!(f, "IndexTableProvider")?;
+        writeln!(f, "---- Index ----")?;
+        write!(f, "{}", self.index)
+    }
+}
+
+impl IndexTableProvider {
+    /// Create a new IndexTableProvider
+    pub async fn try_new(
+        dir: impl Into<PathBuf>,
+        mut index: SQLiteIndex,
+    ) -> anyhow::Result<Self> {
+        let dir = dir.into();
+
+        let files = read_dir(&dir)?;
+        for file in &files {
+            index.add_file(&file.path()).await?;
+        }
+
+        // Get the schema of the first file, assume they all have the same schema
+        let file = files.first().ok_or_else(|| {
+            internal_datafusion_err!("No files found in directory {dir:?}")
+        })?;
+        let file = File::open(file.path()).map_err(|e| {
+            DataFusionError::from(e).context(format!("Error opening file {file:?}"))
+        })?;
+        let reader = ParquetRecordBatchReaderBuilder::try_new(file)?;
+        let schema = reader.schema().clone();
+
+        Ok(Self { index, dir, schema, last_execution: Mutex::new(RefCell::new(SimpleExecutionLog::new())) })
+    }
+}
+
+#[async_trait]
+impl TableProvider for IndexTableProvider {
+    fn as_any(&self) -> &dyn Any {
+        self
+    }
+
+    fn schema(&self) -> SchemaRef {
+        self.schema.clone()
+    }
+
+    fn table_type(&self) -> TableType {
+        TableType::Base
+    }
+
+    async fn scan(
+        &self,
+        state: &SessionState,
+        projection: Option<&Vec<usize>>,
+        filters: &[Expr],
+        limit: Option<usize>,
+    ) -> Result<Arc<dyn ExecutionPlan>> {
+        let df_schema = DFSchema::try_from(self.schema())?;
+
+        // convert filters like [`a = 1`, `b = 2`] to a single filter like `a = 1 AND b = 2`
+        let predicate = conjunction(filters.to_vec());
+        let predicate = predicate
+            .map(|predicate| state.create_physical_expr(predicate, &df_schema))
+            .transpose()?
+            // if there are no filters, use a literal true to have a predicate
+            // that always evaluates to true we can pass to the index
+            .unwrap_or_else(|| datafusion_physical_expr::expressions::lit(true));
+
+        // Use the index to find the files that might have data that matches the
+        // predicate. Any file that can not have data that matches the predicate
+        // will not be returned.
+        let files = self.index.get_files(predicate.clone(), self.schema()).await?;
+
+        // Record the last execution for debugging
+        self.last_execution.lock().unwrap().get_mut().record(files.iter().map(|(filename, plan)| (filename.clone(), plan.access_plan.clone())).collect());
+
+        let object_store_url = ObjectStoreUrl::parse("file://")?;
+        let mut file_scan_config = FileScanConfig::new(object_store_url, self.schema())
+            .with_projection(projection.cloned())
+            .with_limit(limit);
+
+        // Transform to the format needed to pass to ParquetExec
+        // Create one file group per file (default to scanning them all in parallel)
+        for (file_name, file_scan_plan) in files {
+            let path = self.dir.join(file_name);
+            let canonical_path = fs::canonicalize(path)?;
+            file_scan_config = file_scan_config.with_file(
+                PartitionedFile::new(
+                    canonical_path.display().to_string(),
+                    file_scan_plan.file_size,
+                ).with_extensions(Arc::new(file_scan_plan.access_plan))
+            );
+        }
+
+        let exec = ParquetExec::builder(file_scan_config)
+            .with_predicate(predicate)
+            .build_arc();
+
+        Ok(exec)
+    }
+
+    /// Tell DataFusion to push filters down to the scan method
+    fn supports_filters_pushdown(
+        &self,
+        filters: &[&Expr],
+    ) -> Result<Vec<TableProviderFilterPushDown>> {
+        // Inexact because the pruning can't handle all expressions and pruning
+        // is not done at the row level -- there may be rows in returned files
+        // that do not pass the filter
+        Ok(vec![TableProviderFilterPushDown::Inexact; filters.len()])
+    }
+}
+
+impl IndexTableProvider {
+    pub fn last_execution(&self) -> Vec<(String, ParquetAccessPlan)> {
+        self.last_execution.lock().unwrap().borrow().last_execution()
+    }
+}
+
+/// Demonstration Data
+///
+/// Makes a directory with three parquet files
+///
+/// The schema of the files is
+/// * file_name (string)
+/// * value (int32)
+///
+/// The files are as follows:
+/// * file1.parquet (values 0..100)
+/// * file2.parquet (values 100..200)
+/// * file3.parquet (values 200..3000)
+struct DemoData {
+    tmpdir: TempDir,
+}
+
+impl DemoData {
+    fn try_new() -> Result<Self> {
+        let tmpdir = TempDir::new()?;
+        make_demo_file(tmpdir.path().join("file1.parquet"), 0..100)?;
+        make_demo_file(tmpdir.path().join("file2.parquet"), 100..200)?;
+        make_demo_file(tmpdir.path().join("file3.parquet"), 200..3000)?;
+
+        Ok(Self { tmpdir })
+    }
+
+    fn path(&self) -> PathBuf {
+        self.tmpdir.path().into()
+    }
+}
+
+/// Creates a new parquet file at the specified path.
+///
+/// The `value` column  increases sequentially from `min_value` to `max_value`
+/// with the following schema:
+///
+/// * file_name: Utf8
+/// * value: Int32
+/// * text: Utf8
+fn make_demo_file(path: impl AsRef<Path>, value_range: Range<i32>) -> Result<()> {
+    let path = path.as_ref();
+    let file = File::create(path)?;
+    let filename = path
+        .file_name()
+        .ok_or_else(|| internal_datafusion_err!("No filename"))?
+        .to_str()
+        .ok_or_else(|| internal_datafusion_err!("Invalid filename"))?;
+
+    let num_values = value_range.len();
+    let file_names = StringArray::from_iter_values(std::iter::repeat(&filename).take(num_values));
+    let values = Int32Array::from_iter_values(value_range.clone());
+
+    fn int_to_chars(mut n: i32) -> String {
+        let mut result = String::new();
+        while n > 0 {
+            n -= 1;
+            let c = (n % 26) as u8 + b'a';
+            result.push(c as char);
+            n /= 26;
+        }
+        result.chars().rev().collect()
+    }
+
+    let texts: StringArray = value_range
+        .map(int_to_chars)
+        .collect::<Vec<_>>()
+        .into();
+    let batch = RecordBatch::try_from_iter(vec![
+        ("file_name", Arc::new(file_names) as ArrayRef),
+        ("value", Arc::new(values) as ArrayRef),
+        ("text", Arc::new(texts) as ArrayRef),
+    ])?;
+
+    let schema = batch.schema();
+
+    // write the actual values to the file
+    let props = WriterProperties::builder().set_max_row_group_size(50).build();
+    let mut writer = ArrowWriter::try_new(file, schema, Some(props))?;
+    writer.write(&batch)?;
+    writer.finish()?;
+
+    Ok(())
+}
+
+/// Return a list of the directory entries in the given directory, sorted by name
+fn read_dir(dir: &Path) -> Result<Vec<DirEntry>> {
+    let mut files = dir
+        .read_dir()
+        .map_err(|e| DataFusionError::from(e).context(format!("Error reading directory {dir:?}")))?
+        .map(|entry| {
+            entry.map_err(|e| {
+                DataFusionError::from(e)
+                    .context(format!("Error reading directory entry in {dir:?}"))
+            })
+        })
+        .collect::<Result<Vec<DirEntry>>>()?;
+    files.sort_by_key(|entry| entry.file_name());
+    Ok(files)
+}
+
+
+#[derive(Debug, Clone)]
+pub struct SimpleExecutionLog {
+    last_execution: Vec<(String, ParquetAccessPlan)>,
+}
+
+impl SimpleExecutionLog {
+    fn new() -> Self {
+        Self {
+            last_execution: vec![],
+        }
+    }
+
+    fn record(&mut self, plan: Vec<(String, ParquetAccessPlan)>) {
+        self.last_execution = plan;
+    }
+
+    fn last_execution(&self) -> Vec<(String, ParquetAccessPlan)> {
+        self.last_execution.clone()
+    }
+}