use crate::{
metadata::{find_process, list_process_streams_tagged},
metrics_table::metrics_table_schema,
time::ConvertTicks,
};
use super::{
block_partition_spec::BlockPartitionSpec,
jit_partitions::{
generate_jit_partitions, is_jit_partition_up_to_date, write_partition_from_blocks,
},
metrics_block_processor::MetricsBlockProcessor,
partition_source_data::fetch_partition_source_data,
view::{PartitionSpec, View, ViewMetadata},
view_factory::ViewMaker,
};
use anyhow::{Context, Result};
use async_trait::async_trait;
use chrono::{DateTime, Utc};
use datafusion::{
arrow::datatypes::Schema, catalog::TableProvider, execution::context::SessionContext,
};
use micromegas_ingestion::data_lake_connection::DataLakeConnection;
use std::sync::Arc;
use uuid::Uuid;
const VIEW_SET_NAME: &str = "measures";
pub struct MetricsViewMaker {}
impl ViewMaker for MetricsViewMaker {
fn make_view(&self, view_instance_id: &str) -> Result<Arc<dyn View>> {
Ok(Arc::new(MetricsView::new(view_instance_id)?))
}
}
pub struct MetricsView {
view_set_name: Arc<String>,
view_instance_id: Arc<String>,
process_id: Option<sqlx::types::Uuid>,
}
impl MetricsView {
pub fn new(view_instance_id: &str) -> Result<Self> {
let process_id = if view_instance_id == "global" {
None
} else {
Some(Uuid::parse_str(view_instance_id).with_context(|| "Uuid::parse_str")?)
};
Ok(Self {
view_set_name: Arc::new(String::from(VIEW_SET_NAME)),
view_instance_id: Arc::new(view_instance_id.into()),
process_id,
})
}
}
#[async_trait]
impl View for MetricsView {
fn get_view_set_name(&self) -> Arc<String> {
self.view_set_name.clone()
}
fn get_view_instance_id(&self) -> Arc<String> {
self.view_instance_id.clone()
}
async fn make_batch_partition_spec(
&self,
pool: &sqlx::PgPool,
begin_insert: DateTime<Utc>,
end_insert: DateTime<Utc>,
) -> Result<Arc<dyn PartitionSpec>> {
if *self.view_instance_id != "global" {
anyhow::bail!("not supported for jit queries... should it?");
}
let source_data = fetch_partition_source_data(pool, begin_insert, end_insert, "metrics")
.await
.with_context(|| "fetch_partition_source_data")?;
Ok(Arc::new(BlockPartitionSpec {
view_metadata: ViewMetadata {
view_set_name: self.view_set_name.clone(),
view_instance_id: self.view_instance_id.clone(),
file_schema: self.get_file_schema(),
file_schema_hash: self.get_file_schema_hash(),
},
begin_insert,
end_insert,
source_data,
block_processor: Arc::new(MetricsBlockProcessor {}),
}))
}
fn get_file_schema_hash(&self) -> Vec<u8> {
vec![0]
}
fn get_file_schema(&self) -> Arc<Schema> {
Arc::new(metrics_table_schema())
}
async fn jit_update(
&self,
lake: Arc<DataLakeConnection>,
begin_query: DateTime<Utc>,
end_query: DateTime<Utc>,
) -> Result<()> {
if *self.view_instance_id == "global" {
return Ok(());
}
let mut connection = lake.db_pool.acquire().await?;
let process = Arc::new(
find_process(
&mut connection,
&self
.process_id
.with_context(|| "getting a view's process_id")?,
)
.await
.with_context(|| "find_process")?,
);
let streams = list_process_streams_tagged(&mut connection, process.process_id, "metrics")
.await
.with_context(|| "list_process_streams_tagged")?;
let mut all_partitions = vec![];
for stream in streams {
let mut partitions = generate_jit_partitions(
&mut connection,
begin_query,
end_query,
Arc::new(stream),
process.clone(),
)
.await
.with_context(|| "generate_jit_partitions")?;
all_partitions.append(&mut partitions);
}
drop(connection);
let view_meta = ViewMetadata {
view_set_name: self.get_view_set_name(),
view_instance_id: self.get_view_instance_id(),
file_schema_hash: self.get_file_schema_hash(),
file_schema: self.get_file_schema(),
};
let convert_ticks = ConvertTicks::new(&process);
for part in all_partitions {
if !is_jit_partition_up_to_date(&lake.db_pool, view_meta.clone(), &convert_ticks, &part)
.await?
{
write_partition_from_blocks(
lake.clone(),
view_meta.clone(),
part,
Arc::new(MetricsBlockProcessor {}),
)
.await
.with_context(|| "write_partition_from_blocks")?;
}
}
Ok(())
}
async fn make_filtering_table_provider(
&self,
ctx: &SessionContext,
full_table_name: &str,
begin: DateTime<Utc>,
end: DateTime<Utc>,
) -> Result<Arc<dyn TableProvider>> {
let row_filter = ctx
.sql(&format!(
"SELECT * from {full_table_name} WHERE time BETWEEN '{}' AND '{}';",
begin.to_rfc3339(),
end.to_rfc3339(),
))
.await?;
Ok(row_filter.into_view())
}
}