From 19e3ccc6a371b8abeee209908b824516590a02c5 Mon Sep 17 00:00:00 2001 From: SIMRAN MAKHIJA Date: Thu, 2 May 2024 02:33:02 -0400 Subject: [PATCH 1/5] add more tests --- src/handlers/table_handler.rs | 51 +++++++++++++++++++++++++++++++++++ 1 file changed, 51 insertions(+) diff --git a/src/handlers/table_handler.rs b/src/handlers/table_handler.rs index 38d105c..8306c6c 100644 --- a/src/handlers/table_handler.rs +++ b/src/handlers/table_handler.rs @@ -160,6 +160,19 @@ mod tests { StatusCode::CREATED ); + // Test create_table with existing table + assert_eq!( + create_table( + State(repo.clone()), + Path("test".to_string()), + table_creation.clone() + ) + .await + .unwrap_err() + .0, + StatusCode::CONFLICT + ); + // Test table_exists assert_eq!( table_exists( @@ -210,6 +223,32 @@ mod tests { StatusCode::NO_CONTENT ); + // Test rename_table with non-existent source table + let rename_request = Json(TableRenameRequest { + source: TableIdent::new(namespace_ident.clone(), "non_existent".to_string()), + destination: TableIdent::new(namespace_ident.clone(), "table3".to_string()), + }); + assert_eq!( + rename_table(State(repo.clone()), rename_request.clone()) + .await + .unwrap_err() + .0, + StatusCode::NOT_FOUND + ); + + // Test rename_table with existing destination table + let rename_request = Json(TableRenameRequest { + source: TableIdent::new(namespace_ident.clone(), "table2".to_string()), + destination: TableIdent::new(namespace_ident.clone(), "table2".to_string()), + }); + assert_eq!( + rename_table(State(repo.clone()), rename_request.clone()) + .await + .unwrap_err() + .0, + StatusCode::CONFLICT + ); + // Test delete_table assert_eq!( delete_table( @@ -229,5 +268,17 @@ mod tests { .unwrap(), StatusCode::NOT_FOUND ); + + // Test delete_table with non-existent table + assert_eq!( + delete_table( + State(repo.clone()), + Path(("test".to_string(), "non_existent".to_string())) + ) + .await + .unwrap_err() + .0, + StatusCode::NOT_FOUND + ); } } From 45d2c1064dc1534f9aaf9e3ffa9732a3d68d794b Mon Sep 17 00:00:00 2001 From: SIMRAN MAKHIJA Date: Thu, 2 May 2024 03:17:54 -0400 Subject: [PATCH 2/5] docs update --- design_doc.md | 179 +++++++++++++++--------- final_submission.json | 17 +++ test_results/mac/get_namespcae.png | Bin 0 -> 260504 bytes test_results/mac/get_table.png | Bin 0 -> 230763 bytes test_results/mac/list_namespace.png | Bin 0 -> 206834 bytes test_results/mac/list_tables.png | Bin 0 -> 263359 bytes test_results/mac/random.png | Bin 0 -> 233528 bytes test_results/windows/get_namespace.png | Bin 0 -> 104993 bytes test_results/windows/get_table.png | Bin 0 -> 104989 bytes test_results/windows/list_namespace.png | Bin 0 -> 104966 bytes test_results/windows/list_table.png | Bin 0 -> 105033 bytes test_results/windows/random.png | Bin 0 -> 76486 bytes 12 files changed, 132 insertions(+), 64 deletions(-) create mode 100644 final_submission.json create mode 100644 test_results/mac/get_namespcae.png create mode 100644 test_results/mac/get_table.png create mode 100644 test_results/mac/list_namespace.png create mode 100644 test_results/mac/list_tables.png create mode 100644 test_results/mac/random.png create mode 100644 test_results/windows/get_namespace.png create mode 100644 test_results/windows/get_table.png create mode 100644 test_results/windows/list_namespace.png create mode 100644 test_results/windows/list_table.png create mode 100644 test_results/windows/random.png diff --git a/design_doc.md b/design_doc.md index 47deb73..dd9f19b 100644 --- a/design_doc.md +++ b/design_doc.md @@ -29,42 +29,6 @@ A Rust application that exposes a REST API to modify database metadata of the OL We choose RocksDB as the database in the catalog to store metadata. It is a fast and persistent key-value store that can be used as an embedded database for Rust applications. -##### RocksDB Schema - -Column Families - -We use column families for a logical separation and grouping of the metadata store. The - -- Table Data - - Name - string (key) - - Number of columns - u64 - - Read properties - json - - Write properties - json - - File URLs array - string array - - Columns arrays, for each column - - Aggregates - json object - - Range of values - int pair - - Lower bound - - Upper bound - - name - string - - isStrongKey - boolean - - isWeakKey - boolean - - Primary Key col name -- Namespace Data - - Name - string (key) - - Properties - json object -- Operator statistics - - Operator string - string (key) - - Cardinality of prev result - u64 - -#### Tuning/Configuration options - -The catalog can be passed a configuration file at bootstrap with the following configuration options: - -1. data-warehouse-location -2. client-pool-size -3. cache-enabled -4. cache-expiration-interval ## Design Rationale @@ -104,30 +68,17 @@ A detailed description of how you are going to determine that your implementatio For the correctness of the catalog, we plan to conduct unit tests and regression tests. In unit testing, we will test key components and operations such as metadata retrieval, metadata storage, update, and snapshot isolation. -Basic unit tests for handler functions are underway. - -#### Regression tests - -Currently, we plan to conduct regression tests on - -1. Concurrency and parallelism to ensure data integrity -2. Correctness of all the APIs in API spec documentation. -3. Failure Scenarios: Test the behavior and performance under failure scenarios, such as network errors, server failures, or other exceptional conditions. ### Performance testing 1. Concurrency Workloads: Test the performance under concurrent access by simulating multiple clients performing various operations simultaneously (e.g., multiple clients creating tables, querying metadata, committing snapshots, etc.). 2. Large Schemas and Datasets: Evaluate the performance with tables having a large number of columns (e.g., hundreds or thousands of columns) and large datasets with many partitions or snapshots. -3. Bulk Operations: Test the performance of bulk operations like importing or exporting table metadata, snapshots, or partitions. -4. Mixed Workloads: Combine different types of operations in a single workload to simulate a more realistic scenario where various operations are performed concurrently. +3. Mixed Workloads: Combine different types of operations in a single workload to simulate a more realistic scenario where various operations are performed concurrently. ## Trade-offs and Potential Problems +- The biggest trade-off being made in the current design is the absence of any optimizations for updates. Updates to any tables will result in the metadata of the tables stored to become stale. Efficiently updating these values is a design challenge. This has not been prioritized based on the assumption that updates in an OLAP system will be infrequent. -Describe any conscious trade-off you made in your implementation that could be problematic in the future or any problems discovered during the design process that remain unaddressed (technical debts). -The biggest trade-off being made in the current design is the absence of any optimizations for updates. Updates to any tables will result in the metadata of the tables stored to become stale. Efficiently updating these values is a design challenge. This has not been prioritized based on the assumption that updates in an OLAP system will be infrequent. -Organizing the namespaces and tables as prefixes in the keys for the store may cause problems in terms of maintainability. -Database -We chose RocksDB to store metadata, whereas Iceberg Catalog has its own metadata layer that includes metadata files, manifest lists, and manifests. Using RocksDB could be more straightforward to implement compared to building everything from scratch. The components in Iceberg Catalog are likely to be optimized for Iceberg Catalog, and they could outperform RocksDB, which is not dedicated to catalog service. +- We chose RocksDB to store metadata, whereas Iceberg Catalog has its own metadata layer that includes metadata files, manifest lists, and manifests. Using RocksDB could be more straightforward to implement compared to building everything from scratch. The components in Iceberg Catalog are likely to be optimized for Iceberg Catalog, and they could outperform RocksDB, which is not dedicated to catalog service. ## Support for Parallelism Our catalog service is designed to support parallelism to enhance performance. This is achieved through the following ways: @@ -135,26 +86,126 @@ Our catalog service is designed to support parallelism to enhance performance. T 2. **Asynchronous API**: The REST API exposed by our Rust application is asynchronous, meaning it can handle multiple requests at the same time without blocking. This is particularly useful for operations that are I/O-bound, such as reading from or writing to the database. -3. **Thread Pool**: We plan to use a thread pool for handling requests. This allows us to limit the number of threads used by our application, preventing thread thrashing and improving performance. ## Performance Tuning Plan Performance tuning is crucial for the efficiency and speed of our catalog service. Here's our plan: -1. **RocksDB Tuning**: We will tune RocksDB configurations based on our workload. For example, we can adjust the block cache size, write buffer size, and compaction style to optimize for read-heavy or write-heavy workloads. More details can be found in the [RocksDB Tuning Guide](https://github.com/facebook/rocksdb/wiki/RocksDB-Tuning-Guide). - -2. **API Optimization**: We will monitor the performance of our API endpoints and optimize the slow ones. This will involve optimizing the database access methods and refactoring the code. +1. **API Optimization**: We will monitor the performance of our API endpoints and optimize the slow ones. This will involve optimizing the database access methods and refactoring the code. -3. **Load Testing**: We will conduct load testing to understand how our service performs under heavy load. This will help us identify bottlenecks and areas for improvement. - -4. **Monitoring and Metrics**: We will add monitoring and metrics to our service to track performance over time. This will help us identify performance regressions and understand the impact of our tuning efforts. +1. **Load Testing**: We will conduct load testing to understand how our service performs under heavy load. This will help us identify bottlenecks and areas for improvement. ## Milestones -- 75%: Basic API support -- 100%: Support for parallelism and performance tuning -- 125%: Performance testing against Iceberg Catalog - - +:white_check_mark: 75%: Basic API support +:white_check_mark: 100%: Support for parallelism and performance tuning +:white_check_mark: 125%: Performance testing ~~against Iceberg Catalog~~ + +## Performance Testing Results + +**Command to run benchmark script** +```sh +python3 benchmarking/bench.py -b catalog1 -d ../rocksdb -u http://localhost:3000 -n 100 -t 1000 -r 1000 -p +``` + +### Windows +#### Host Specifications +``` +OS: Windows 11 Home x86_64 +Host: HP OMEN Laptop 15-en0xxx +Kernel: 10.0.22631 +CPU: AMD Ryzen 7 4800H with Radeon Graphics (16) @ 2.900GHz +GPU: Caption +GPU: AMD Radeon(TM) Graphics +GPU: NVIDIA GeForce GTX 1660 Ti +Memory: 13769MiB / 15731MiB +``` +#### Get Namespace API +``` +Requests [total, rate, throughput] 9991, 999.20, 999.20 +Duration [total, attack, wait] 9.9989534s, 9.9989534s, 0s +Latencies [mean, 50, 95, 99, max] 860.52µs, 972.607µs, 1.452413ms, 2.987446ms, 37.2744ms +``` +![](./test_results/windows/get_namespace.png) + +#### Get Table API +``` +Requests [total, rate, throughput] 10000, 999.55, 999.55 +Duration [total, attack, wait] 10.004488s, 10.004488s, 0s +Latencies [mean, 50, 95, 99, max] 865.783µs, 972.728µs, 1.418071ms, 3.01372ms, 37.3176ms +``` +![](./test_results/windows/get_table.png) + +#### List Namespace API +``` +Requests [total, rate, throughput] 10000, 1001.10, 1001.05 +Duration [total, attack, wait] 9.9895398s, 9.9890283s, 511.5µs +Latencies [mean, 50, 95, 99, max] 1.883553ms, 1.191091ms, 5.006752ms, 8.196381ms, 43.6933ms +``` +![](./test_results/windows/list_namespace.png) +#### List Tables API +``` +Requests [total, rate, throughput] 9992, 999.50, 999.50 +Duration [total, attack, wait] 9.9970348s, 9.9970348s, 0s +Latencies [mean, 50, 95, 99, max] 971.232µs, 973.659µs, 1.978657ms, 3.292131ms, 45.7625ms +``` +![](./test_results/windows/list_table.png) +#### Random Testing +``` +Requests [total, rate, throughput] 59995, 1000.02, 1000.02 +Duration [total, attack, wait] 59.9940374s, 59.9940374s, 0s +Latencies [mean, 50, 95, 99, max] 526.566µs, 522.409µs, 1.027574ms, 2.010563ms, 23.165ms +``` +![](./test_results/windows/random.png) +### MacBook Air M1 +#### Host Specifications +``` +OS: macOS 14.4.1 23E224 arm64 +Host: MacBookAir10,1 +Kernel: 23.4.0 +WM: Quartz Compositor +WM Theme: Blue (Dark) +Terminal: vscode +CPU: Apple M1 +GPU: Apple M1 +Memory: 1514MiB / 8192MiB +``` + +#### Get Namespace API +``` +Requests [total, rate, throughput] 10000, 1000.10, 1000.08 +Duration [total, attack, wait] 9.999s, 9.999s, 213µs +Latencies [min, mean, 50, 90, 95, 99, max] 65.833µs, 191.877µs, 196.477µs, 243.657µs, 256.028µs, 305.26µs, 1.578ms + +``` +![](./test_results/mac/get_namespcae.png) +#### Get Table API +``` +Requests [total, rate, throughput] 10000, 1000.10, 999.27 +Duration [total, attack, wait] 9.999s, 9.999s, 268.708µs +Latencies [min, mean, 50, 90, 95, 99, max] 70.166µs, 221.648µs, 223.806µs, 262.714µs, 279.431µs, 394.982µs, 6.708ms +``` +![](./test_results/mac/get_table.png) +#### List Namespace API +``` +Requests [total, rate, throughput] 10000, 1000.11, 999.16 +Duration [total, attack, wait] 9.999s, 9.999s, 498.75µs +Latencies [min, mean, 50, 90, 95, 99, max] 272.708µs, 478.628µs, 452.66µs, 580.816µs, 605.989µs, 726.08µs, 18.557ms +``` +![](./test_results/mac/list_namespace.png) +#### List Tables API +``` +Requests [total, rate, throughput] 10000, 1000.10, 999.97 +Duration [total, attack, wait] 9.999s, 9.999s, 254.458µs +Latencies [min, mean, 50, 90, 95, 99, max] 73.625µs, 235.993µs, 249.85µs, 283.297µs, 296.26µs, 365.961µs, 1.97ms +``` +![](./test_results/mac/list_tables.png) +#### Random Testing +``` +Requests [total, rate, throughput] 60000, 1000.02, 999.93 +Duration [total, attack, wait] 59.999s, 59.999s, 86.666µs +Latencies [min, mean, 50, 90, 95, 99, max] 54.708µs, 186.655µs, 171.961µs, 252.694µs, 278.067µs, 429.093µs, 14.688ms +``` +![](./test_results/mac/random.png) ### References [1] https://www.snowflake.com/blog/how-foundationdb-powers-snowflake-metadata-forward/ diff --git a/final_submission.json b/final_submission.json new file mode 100644 index 0000000..a0bf82b --- /dev/null +++ b/final_submission.json @@ -0,0 +1,17 @@ +{ + "info": { + "title": "OLAP System Catalog", + "github": "https://github.com/cmu-db/15721-s24-catalog1", + "description": "We developed a metadata catalog to help the query optimizer in modern OLAP systems, which need efficient metadata management for analytic queries. Our Rust application uses RocksDB for metadata storage, exposing a REST API for interaction. The architecture includes a data model, database, service, and controller layers, ensuring seamless metadata management. RocksDB's key-value store, chosen for its concurrency and scalability, outperformed SQLite for our needs. Axum powers our REST API for efficient asynchronous operations. Testing ensures the catalog's correctness and performance, with a design focused on optimizing read performance over frequent updates.", + "students": [ + { + "name": "Aditya Ajmera", + "url": "https://www.linkedin.com/in/adityaajmera/" + }, + { + "name": "Simran Makhija", + "url": "https://www.linkedin.com/in/simran-makhija/" + } + ] + } +} \ No newline at end of file diff --git a/test_results/mac/get_namespcae.png b/test_results/mac/get_namespcae.png new file mode 100644 index 0000000000000000000000000000000000000000..dcd011e3920c6b511771bb8217da710e6e71aba7 GIT binary patch literal 260504 zcmeFacU;q1w>}y|=txySr70>3QfweSii#DmAf12>6%eI}w3JanLBR?tC9#4cMFB-x z5Cl{dkg6yI5Ty4Sl90Q;=y>KmlbLtsoOwU@cYinkIL>w_*=6mu)_(SS);e!#ZZ=DJ zo-hi9nzd!~hFvI>2o{Cnw-e-tmd&-Tj_@BI?_Fl=Q7Pr}T_}_?YRiUodrmp^HVS3L zSp}OgA%bj~R zNp4(bC9g~oyf5RsLe1sM+^gFBSFj49EQf@$Gpa%1?|lMGS&8PSs8_2A zEdCn{57Q|?Wf=UuPY|&OF``)O2UcQR|N0gq3rFNR?DzLRfg-(y9ZuPvB!BHM3)A;4 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zagRb1I9PQ7G7)ATV#;T$bBXwPo?Yf`2j?v|_jU%aG?Cxh1%x0H1cC~{6Er7|5B9_Q zoPhJg29Bm?`TMp#?&l~d=LvdMj{I$1nzHnnD8NBj1kyw1bTf{S)FO^f*uIZg{O5h; zH>=I@IO|4bHZ|vGYxltITmK!Y0TYmI`sYDe{oEIGB*caT{HQ8vD8l3|Uj84r(%F~* literal 0 HcmV?d00001 From a1483ecd6571ca8f8421a0525c952b9d45639041 Mon Sep 17 00:00:00 2001 From: SIMRAN MAKHIJA Date: Thu, 2 May 2024 05:07:39 -0400 Subject: [PATCH 3/5] update doc --- design_doc.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/design_doc.md b/design_doc.md index dd9f19b..6d5c13b 100644 --- a/design_doc.md +++ b/design_doc.md @@ -32,7 +32,6 @@ We choose RocksDB as the database in the catalog to store metadata. It is a fast ## Design Rationale -An explanation of why you chose the given design. Your justification should discuss issues related to (1) correctness, (2) performance, (3) engineering complexity/maintainability, and (4) testing. It should also include a brief discussion of the other implementations that you considered and why they were deemed inferior. Most design decisions were made with the assumption that we do not have any schema updates and writes are infrequent with bulk data #### Database @@ -42,7 +41,6 @@ We contemplated two embedded database candidates for catalog service: SQLite and 1. Better concurrency control: SQLite locks the entire database when dealing with concurrency writing, whereas RocksDB supports snapshots. 2. Flexibility: RocksDB provides more configuration options. 3. Scalability: RocksDB stores data in different partitions, whereas SQLite stores data in one single file, which isn’t ideal for scalability. -4. Storage: RocksDB uses key-value storage, which is good for intensive write operations. In short, RocksDB would provide better performance and concurrency control when we deal with write-intensive workloads. #### Why a key-value store? @@ -142,6 +140,7 @@ Duration [total, attack, wait] 9.9895398s, 9.9890283s, 511.5µs Latencies [mean, 50, 95, 99, max] 1.883553ms, 1.191091ms, 5.006752ms, 8.196381ms, 43.6933ms ``` ![](./test_results/windows/list_namespace.png) + #### List Tables API ``` Requests [total, rate, throughput] 9992, 999.50, 999.50 @@ -149,6 +148,7 @@ Duration [total, attack, wait] 9.9970348s, 9.9970348s, 0s Latencies [mean, 50, 95, 99, max] 971.232µs, 973.659µs, 1.978657ms, 3.292131ms, 45.7625ms ``` ![](./test_results/windows/list_table.png) + #### Random Testing ``` Requests [total, rate, throughput] 59995, 1000.02, 1000.02 From cf621c29687a3fa17ce0a6057f874545c91d048e Mon Sep 17 00:00:00 2001 From: SIMRAN MAKHIJA Date: Thu, 2 May 2024 05:35:55 -0400 Subject: [PATCH 4/5] cleanup --- src/dto/errors.rs | 137 ------------------------------ src/dto/mod.rs | 1 - src/handlers/namespace_handler.rs | 2 - 3 files changed, 140 deletions(-) delete mode 100644 src/dto/errors.rs diff --git a/src/dto/errors.rs b/src/dto/errors.rs deleted file mode 100644 index 7811a66..0000000 --- a/src/dto/errors.rs +++ /dev/null @@ -1,137 +0,0 @@ -use serde::{Deserialize, Serialize}; -use std::fmt::Debug; - -#[derive(Debug, Deserialize, Serialize)] -pub struct NamespaceNotFoundError { - pub message: String, -} - -impl From for IcebergErrorResponse { - fn from(err: NamespaceNotFoundError) -> Self { - IcebergErrorResponse { - error: ErrorModel { - message: err.message, - r#type: "NamespaceNotFound".to_string(), - code: 404, - stack: None, - }, - } - } -} - -#[derive(Debug, Deserialize, Serialize)] -pub struct ErrorModel { - pub message: String, - pub r#type: String, // Use `r#type` to avoid keyword conflict - pub code: u16, - #[serde(skip_serializing_if = "Option::is_none")] - pub stack: Option>, -} - -#[derive(Debug, Deserialize, Serialize)] -pub struct IcebergErrorResponse { - pub error: ErrorModel, -} - -#[derive(Debug, Deserialize, Serialize)] -pub struct CommonResponse { - pub error: Option, -} - -#[derive(Debug, Deserialize, Serialize)] -pub struct BadRequestErrorResponse(pub CommonResponse); - -#[derive(Debug, Deserialize, Serialize)] -pub struct UnsupportedOperationResponse(pub CommonResponse); - -#[derive(Debug, Deserialize, Serialize)] -pub struct ServiceUnavailableResponse(pub CommonResponse); - -#[derive(Debug, Deserialize, Serialize)] -pub struct ServerErrorResponse(pub CommonResponse); - -#[derive(Debug, Deserialize, Serialize)] -pub enum ErrorTypes { - BadRequest(String), - Unauthorized(String), - ServiceUnavailable(String), - ServerError(String), - NamespaceNotFound(String), -} - -impl std::fmt::Display for ErrorTypes { - fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { - match self { - ErrorTypes::BadRequest(msg) => write!(f, "Bad Request: {}", msg), - ErrorTypes::Unauthorized(msg) => write!(f, "Unauthorized: {}", msg), - ErrorTypes::ServiceUnavailable(msg) => write!(f, "Service Unavailable: {}", msg), - ErrorTypes::ServerError(msg) => write!(f, "Internal Server Error: {}", msg), - ErrorTypes::NamespaceNotFound(msg) => write!(f, "Namespace Not Found: {}", msg), - } - } -} - -#[cfg(test)] -mod tests { - use super::*; - use serde_json::{json, Value}; - - #[test] - fn test_namespace_not_found_error() { - let err = NamespaceNotFoundError { - message: "Namespace 'test' not found".to_string(), - }; - let iceberg_err: IcebergErrorResponse = err.into(); - - assert_eq!(iceberg_err.error.message, "Namespace 'test' not found"); - assert_eq!(iceberg_err.error.r#type, "NamespaceNotFound"); - assert_eq!(iceberg_err.error.code, 404); - assert!(iceberg_err.error.stack.is_none()); - } - - #[test] - fn test_error_model_deserialization() { - let json_str = r#"{ - "message": "Bad request", - "type": "BadRequest", - "code": 400, - "stack": null - }"#; - - let error_model: ErrorModel = serde_json::from_str(json_str).unwrap(); - - assert_eq!(error_model.message, "Bad request"); - assert_eq!(error_model.r#type, "BadRequest"); - assert_eq!(error_model.code, 400); - assert!(error_model.stack.is_none()); - } - - #[test] - fn test_error_types_display() { - let bad_request = ErrorTypes::BadRequest("Invalid request body".to_string()); - let unauthorized = ErrorTypes::Unauthorized("Missing authentication token".to_string()); - let service_unavailable = - ErrorTypes::ServiceUnavailable("Server is under maintenance".to_string()); - let server_error = ErrorTypes::ServerError("Internal server error".to_string()); - let namespace_not_found = - ErrorTypes::NamespaceNotFound("Namespace 'test' not found".to_string()); - - assert_eq!(bad_request.to_string(), "Bad Request: Invalid request body"); - assert_eq!( - unauthorized.to_string(), - "Unauthorized: Missing authentication token" - ); - assert_eq!( - service_unavailable.to_string(), - "Service Unavailable: Server is under maintenance" - ); - assert_eq!( - server_error.to_string(), - "Internal Server Error: Internal server error" - ); - assert_eq!( - namespace_not_found.to_string(), - "Namespace Not Found: Namespace 'test' not found" - ); - } -} diff --git a/src/dto/mod.rs b/src/dto/mod.rs index bf04b8b..98f2086 100644 --- a/src/dto/mod.rs +++ b/src/dto/mod.rs @@ -1,5 +1,4 @@ pub mod column_data; -pub mod errors; pub mod namespace_data; pub mod rename_request; pub mod set_namespace_properties_req; diff --git a/src/handlers/namespace_handler.rs b/src/handlers/namespace_handler.rs index abacbf0..f6ff209 100644 --- a/src/handlers/namespace_handler.rs +++ b/src/handlers/namespace_handler.rs @@ -144,8 +144,6 @@ mod tests { #[tokio::test] async fn test_namespace_endpoints() { let dir = tempdir().unwrap(); - let db = Database::open(dir.path()).unwrap(); - let db = Arc::new(Mutex::new(db)); let repo = Arc::new(NamespaceRepository::new(Arc::new(Mutex::new( Database::open(tempdir().unwrap().path()).unwrap(), )))); From a06ed308f2a2cedef67f2a22ff127eec6e7e1937 Mon Sep 17 00:00:00 2001 From: SIMRAN MAKHIJA Date: Thu, 2 May 2024 05:36:17 -0400 Subject: [PATCH 5/5] cleanup --- src/handlers/namespace_handler.rs | 1 - 1 file changed, 1 deletion(-) diff --git a/src/handlers/namespace_handler.rs b/src/handlers/namespace_handler.rs index f6ff209..f7a365f 100644 --- a/src/handlers/namespace_handler.rs +++ b/src/handlers/namespace_handler.rs @@ -143,7 +143,6 @@ mod tests { use tempfile::tempdir; #[tokio::test] async fn test_namespace_endpoints() { - let dir = tempdir().unwrap(); let repo = Arc::new(NamespaceRepository::new(Arc::new(Mutex::new( Database::open(tempdir().unwrap().path()).unwrap(), ))));