less {filename}
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-- show running queries (pre 9.2) | |
SELECT procpid, age(clock_timestamp(), query_start), usename, current_query | |
FROM pg_stat_activity | |
WHERE current_query != '<IDLE>' AND current_query NOT ILIKE '%pg_stat_activity%' | |
ORDER BY query_start desc; | |
-- show running queries (9.2) | |
SELECT pid, age(clock_timestamp(), query_start), usename, query | |
FROM pg_stat_activity | |
WHERE query != '<IDLE>' AND query NOT ILIKE '%pg_stat_activity%' |
#!/usr/bin/env bash | |
FILENAME=${1} | |
# expected to be defined in the environment | |
# - AZURE_STORAGE_ACCOUNT | |
# - AZURE_CONTAINER_NAME | |
# - AZURE_ACCESS_KEY | |
# inspired by |
Custom recipe to get full Node.js Cloud Environment in DigitalOcean Dokku droplet running from scratch. Yes. Your own Heroku for $5 per month.
I use this gist to keep track of the important configuration steps required to have a functioning system after fresh install.
When you have executed that's all step by step you will get a new working and stable system which is ready to host & serve your Node.js application and databases.
# Spark Streaming Logging Configuration | |
# See also: http://spark.apache.org/docs/2.0.2/running-on-yarn.html#debugging-your-application | |
log4j.rootLogger=INFO, stderr | |
# application namespace configuration | |
log4j.logger.de.inovex.mysparkapp=stderr, stdout | |
# Write all logs to standard Spark stderr file | |
log4j.appender.stderr=org.apache.log4j.RollingFileAppender |