Problem: the approximate method can still be slow for many trees
catboost version: master
Operating System: ubuntu 18.04
CPU: i9
GPU: RTX2080

Would be good to be able to specify how many trees to use for shapley. The model.predict and prediction_type versions allow this. lgbm/xgb allow this.

change all x-moloch-cookies to x-arkime-cookies in tests and middleware 😋

There is no technical difficulty to support includeValue option, looks like we are just missing it on the API level.

See SO question

... to make it easier to read Vespa documentation on an e-reader / offline

Vespa documentation is generated using Jekyll from .md and .html files, look into options for generating the artifact as part of site generation (there might be plugins we can use here)

Hi, if my spark app is using 2 storage type, both S3 and Azure Data Lake Store Gen2, could I put spark.delta.logStore.class=org.apache.spark.sql.delta.storage.AzureLogStore, org.apache.spark.sql.delta.storage.S3SingleDriverLogStore

Thanks in advance

From https://trinodb.slack.com/archives/CFLB9AMBN/p1619569057404100

This does not work

jmx.dump-tables="java.lang:type=GarbageCollector,name=g1 old Generation"

You need to escape the commas, which are used to separate multiple table names. Try with:

jmx.dump-tables=java.lang:type=GarbageCollector\,name=g1 old Generation

Use case:
Right now one can only use date_trunc() to easily define time buckets. date_trunc() only supports predefine time intervals like 1 minute, 1 hour, etc. . In time-series use cases it is often necessary to define different time bucket sizes like e.g. '5 minutes' or '20 minutes'

a workaround for this is the - error prone - integer division on the timestamp e.g.

S