rapids/docs/usage/faq.rst

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Frequently Asked Questions
============================
1. Cannot connect to the MySQL server
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**Error in .local(drv, ...) :**
**Failed to connect to database: Error: Can't initialize character set unknown (path: compiled_in)**
::
Calls: dbConnect -> dbConnect -> .local -> .Call
Execution halted
[Tue Mar 10 19:40:15 2020]
Error in rule download_dataset:
jobid: 531
output: data/raw/p60/locations_raw.csv
RuleException:
CalledProcessError in line 20 of /home/ubuntu/rapids/rules/preprocessing.snakefile:
Command 'set -euo pipefail; Rscript --vanilla /home/ubuntu/rapids/.snakemake/scripts/tmp_2jnvqs7.download_dataset.R' returned non-zero exit status 1.
File "/home/ubuntu/rapids/rules/preprocessing.snakefile", line 20, in __rule_download_dataset
File "/home/ubuntu/anaconda3/envs/moshi-env/lib/python3.7/concurrent/futures/thread.py", line 57, in run
Shutting down, this might take some time.
Exiting because a job execution failed. Look above for error message
**Solution:**
Please make sure the ``MY_GROUP`` in ``config.yaml`` and ``.env`` match.
2. Cannot start mysql in linux via ``brew services start mysql``
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use the following command instead:
``mysql.server start``
3. Every time I run ``snakemake -R download_dataset`` all rules are executed
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This is expected behavior. The advantage of using ``snakemake`` under the hood is that every time a file containing data is modified every rule that depends on that file will be re-executed to update their results. In this case, since ``download_dataset`` updates all the raw data, and you are forcing the rule with the flag ``-R`` every single rule that depends on those raw files will be executed.
4. Got an error ``Table XXX doesn't exist`` while running the download_dataset rule.
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::
Error in .local(conn, statement, ...) :
could not run statement: Table 'db_name.table_name' doesn't exist
Calls: colnames ... .local -> dbSendQuery -> dbSendQuery -> .local -> .Call
Execution halted
**Solution:**
Please make sure the sensors listed in SENSORS in ``config.yaml`` match your database tables.