Shantanu's Blog

Corporate Consultant

April 30, 2019

 

elastic watcher alerts

Here is the code to set email alerts when an event occur.

# install watcher plugin

bin/plugin install elasticsearch/license/latest
bin/plugin install elasticsearch/watcher/latest

# add email section to elasticsearch.yml file

watcher.actions.email.service.account:
    gmail_account:
        profile: gmail
        smtp:
            auth: true
            starttls.enable: true
            host: smtp.gmail.com
            port: 587
            user: shantanu.XXX
            password: XXX

# re-start elasticsearch and add a watcher document

curl -XPUT 'http://1.2.3.4:9200/_watcher/watch/log_event_watch' -d '{
  "metadata" : {
    "color" : "red"
  },
  "trigger" : {
    "schedule" : {
      "interval" : "5m"
    }
  },
  "input" : {
    "search" : {
      "request" : {
        "indices" : "packet*",
        "body" : {
          "size" : 0,
          "query" : { "match" : { "status" : "error" } }
        }
      }
    }
  },
  "condition" : {
    "script" : "return ctx.payload.hits.total > 5"
  },
  "actions" : {
    "email_administrator" : {
      "throttle_period": "15m",
      "email" : {
        "to" : "shantanu1234@gmail.com",
        "subject" : "Encountered {{ctx.payload.hits.total}} errors",
        "body" : "Too many error in the system, see attached data",
        "attachments" : {
          "attached_data" : {
            "data" : {
              "format" : "json"
            }
          }
        },
        "priority" : "high"
      }

    }
  }
}'

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April 28, 2019

 

MySQL error log using Elastic stack

Here are 3 easy steps to enable mysql failed query log.
1) Download packetbeat config file
2) Edit config file to add "send_response" parameter
3) Start docker container

# download packetbeat config file
curl -L -O https://raw.githubusercontent.com/elastic/beats/7.0/deploy/docker/packetbeat.docker.yml

# add send_response parameter to mysql
packetbeat.protocols.mysql:
  ports: [3306]
  send_response: true

# start docker container
docker run \
  --user=packetbeat \
  --volume="$(pwd)/packetbeat.docker.yml:/usr/share/packetbeat/packetbeat.yml:ro" \
  --cap-add="NET_RAW" \
  --cap-add="NET_ADMIN" \
  --network=host \
  -d docker.elastic.co/beats/packetbeat:7.0.0 \
  --strict.perms=false -e \
  -E cloud.id=XXX \
  -E cloud.auth=elastic:XXX

# Once you get logs in Kibana, use a filter type:mysql and status:Error to extract failing queries.

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April 12, 2019

 

Entity recognition using spacy

python module spacy can be used for named entity recognition.

from spacy.lang.en import English
from spacy.matcher import PhraseMatcher

nlp = English()
matcher = PhraseMatcher(nlp.vocab, attr="LOWER")

phrases = ['machine learning', 'robots', 'intelligent agents']
patterns = [nlp.make_doc(text) for text in phrases] 
matcher.add("Names", None, *patterns)

processed_article = 'This is all about machine learning and robots'
sentence = nlp(processed_article)

for match_id, start, end in matcher(sentence):
    print("Matched based on lowercase token text:", sentence[start:end])

The output will be...
Matched based on lowercase token text: machine learning
Matched based on lowercase token text: robots

Labels:


April 05, 2019

 

Symbolic Link file for Athena


Athena can read only dictionary and not the actual file. You need to save all .csv.gz files in a folder or sub-folder without any other data. This requirement makes it impossible to use Athena when you are storing all your files in one place. You can use symbolic link file to connect to different files and read them all together in a single table. Let’s assume we need to read these 2 files...

# cat symlink.txt
s3://your_bucket/some_folder/bulk_data.csv.gz
s3://another_bucket/month_jan/more_data.csv.gz

We are creating a list of all files having the same format (csv.gz and X number of columns in all csv) Now we will name the file as “symlink.txt” and upload it in it’s own folder.

# aws s3 cp symlink.txt s3://132cols/symlink/

Create a regular athena table with location pointing to symbolic link file. But we need to declare that the location is symbolic and that is possible with “stored as inputformat” paramter that is followed by outputformat.

CREATE EXTERNAL TABLE `customers`(
`cust_id` string,
`status` string,
`deliver_date` string,
`batch_id` string,
`date_current` string,
`user_name` string,
`sp_id` string,
`delivery_datetime` string,
`service_name` string,
`sm_id` string,
`m_count` string,
`err_code` string,
`customer_response` string)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.OpenCSVSerde'
WITH SERDEPROPERTIES (
'serialization.format' = ',',
'field.delim' = ',',
"quoteChar" = "\""
)
STORED AS INPUTFORMAT 'org.apache.hadoop.hive.ql.io.SymlinkTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.IgnoreKeyTextOutputFormat'
LOCATION 's3://132cols/symlink/'
TBLPROPERTIES ('has_encrypted_data'='false')

Now we can query the table that will load the data mentioned in symbolic file. We can also use sql workbench to access athena.


The instructions to configure workbench for athena are here…


and here as well...


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