From 01d391f5c2b0e017b08040b9adc81b0c78cf1f71 Mon Sep 17 00:00:00 2001 From: Parashar Shah <17348989+parasharshah@users.noreply.github.com> Date: Fri, 30 Nov 2018 11:14:49 -0800 Subject: [PATCH] updated table --- databricks/automl_adb_readme.md | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/databricks/automl_adb_readme.md b/databricks/automl_adb_readme.md index 600a4cc8..d3f21735 100644 --- a/databricks/automl_adb_readme.md +++ b/databricks/automl_adb_readme.md @@ -17,22 +17,21 @@ Select New Cluster and fill in following detail: - Databricks Runtime: Any 4.* runtime (NO GPU) or Recommended: 4.3(includes Apache spark 2.3.1, Scala 2.11)) - Python version: **3** - Driver type – you may select a small driver node size (eg. Standard_DS3_v2 0.75 DBU) - - Worker node VM types: Memory optimized preferred. Please follow this table. + - Worker node VM types: **Memory optimized VM** preferred. Please follow this table. |**Dataset type** | **Dataset size** |**Preprocessed dataset size** | **Number of cross validations (cv)** |**Recommended memory per concurrency for VM**|**Total memory required for cluster** | |--|--|--|--|--|--| -|String & Numeric | X |3X | 3 * X * cv |3 * X * cv * 3 | 3 * X * cv * 3 * number of concurrent runs | -|Numeric | Y |Y| Y |3Y| 3 * Y * number of concurrent runs | +|String & Numeric (preprocessing True) | X |5 * X | 5 * X * cv |5 * X * cv * 3 | 5 * X * cv * 3 * number of concurrent runs | +|Numeric (preprocessing False) | Y |1.5 * Y| 1.5 * Y |5 * Y| 5 * Y * number of concurrent runs | +|Numeric (preprocessing True) | Y |1.5 * Y| 1.5 * Y * cv |5 * Y * cv| 5 * cv * Y * number of concurrent runs | -- Number of concurrent runs should be less than or equal to the number -of cores in your Databricks cluster. +- Number of concurrent runs should be less than or equal to the number of cores in your Databricks cluster. - For a 1 GB numeric only dataset, to do 10 cross validations with run 16 concurrent runs, the minimum usable cluster memory should be 1 GB X 16 concurrent runs X 3 = 48 GB. This is in addition to what Spark itself will use on your cluster. -- For text dataset, with featurization (eg. one hot encoding) & cross validation this requirement is much higher. For a 500 MB -string+numeric dataset, to do 5 cross validation with 4 concurrent -runs, the minimum usable cluster memory should be 0.5 GB X 4 +- For string & numeric dataset, with featurization (eg. one hot encoding) & cross validation this requirement is much higher. For a 500 MB string+numeric dataset, to do 5 cross validation with 4 concurrent runs, the minimum usable cluster memory should be 0.5 GB X 4 concurrent runs X 3 X 5 cross validations X 3 = 90 GB +- For text dataset, TBD. - Uncheck _Enable Autoscaling_ - Workers: 2 or higher