From a016a45178fa0305e8dcb796c8b16b1688932e59 Mon Sep 17 00:00:00 2001 From: Lixi Zhou Date: Fri, 1 Sep 2023 20:53:32 -0700 Subject: [PATCH] update link --- DeepMapping/DeepMapping/benchmark_utils.py | 9 ++++++--- README.md | 8 ++++---- 2 files changed, 10 insertions(+), 7 deletions(-) diff --git a/DeepMapping/DeepMapping/benchmark_utils.py b/DeepMapping/DeepMapping/benchmark_utils.py index 82cae55..7974713 100644 --- a/DeepMapping/DeepMapping/benchmark_utils.py +++ b/DeepMapping/DeepMapping/benchmark_utils.py @@ -1,4 +1,4 @@ -from DeepMapping import dgpe_compression, byte_dictionary_compression, delta_compression, lzo_compression, zstd_compression, uncompress, rle_compression, deepmapping +from DeepMapping import dgpe_compression, byte_dictionary_compression, delta_compression, lzo_compression, zstd_compression, uncompress, rle_compression, deepmapping, hashtable, hashtable_with_compression def benchmark_handler(benchmark, bench_type='single'): @@ -19,10 +19,13 @@ def benchmark_handler(benchmark, bench_type='single'): return zstd_compression.measure_latency elif benchmark == "rle": return rle_compression.measure_latency + elif benchmark == 'hashtable': + return hashtable.measure_latency + elif benchmark == 'hashtable_with_compression': + return hashtable_with_compression.measure_latency elif benchmark == "deepmapping": return deepmapping.measure_latency_any else: raise ValueError("NON-EXIST benchmark") else: - raise ValueError("Non supported bench_type") - \ No newline at end of file + raise ValueError("Non supported bench_type") \ No newline at end of file diff --git a/README.md b/README.md index 33e2d66..fa97581 100644 --- a/README.md +++ b/README.md @@ -27,9 +27,9 @@ Resources for SIGMOD 2024 Submission ## Dataset -Our experiments covered synthetic datasets, low/high correlation datasets with different scales(100MB, 1GB, 10GB), and TPC-H, TPC-DS benchmark datasets with scale factors as 1 and 10. We removed all string/continuous columns and uploaded our pre-generated datasets to [**HERE**](#FIXME): +Our experiments covered synthetic datasets, low/high correlation datasets with different scales(100MB, 1GB, 10GB), and TPC-H, TPC-DS benchmark datasets with scale factors as 1 and 10. We removed all string/continuous columns and uploaded our pre-generated datasets to [**HERE**](https://mega.nz/file/nNggnQzA#9Ma2v3GIrfR-3ndGNzGXsF5ZOcWtGwZKeRekUiqOnzA): -[**DATA LINK: Uploading...**](#FIXME) +[**DATA LINK: Here**](https://mega.nz/file/nNggnQzA#9Ma2v3GIrfR-3ndGNzGXsF5ZOcWtGwZKeRekUiqOnzA) After download it, please unzip it to the **root** folder of this GitHub repository. Then, you will see a **dataset** folder here. @@ -48,9 +48,9 @@ List of datasets: ## Benchmark -We provided some example models for the following 2 tasks. Please go [**HERE**](#FIXME) to download: +We provided some example models for the following 2 tasks. Please go [**HERE**](https://mega.nz/file/icxG1JaL#cuC5C4_PxQ1FsgSUmswfaXyzCaatOwx9n_b9F_-IDnU) to download: -[**MODEL LINK: Uploading...**](#FIXME) +[**MODEL LINK: Here**](https://mega.nz/file/icxG1JaL#cuC5C4_PxQ1FsgSUmswfaXyzCaatOwx9n_b9F_-IDnU) After download it, please unzip it to the **root** folder of this GitHub repository. Then, you will see a **models** folder here.