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- Permission Management
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- Collection Overview
- Collecting Logs in Self-Built Kubernetes Cluster
- Collecting Syslog
- Collection by LogListener
- Collecting Text Log
- Uploading Log over Kafka
- Uploading Logs via Anonymous Write
- Uploading Logs via Logback Appender
- Uploading Logs via Log4j Appender
- Uploading Log via SDK
- Uploading Log via API
- Importing Data
- Tencent Cloud Service Log Access
- Metric Collection
- Log Storage
- Metric Storage
- Search and Analysis (Log Topic)
- Syntax and Rules
- Statistical Analysis (SQL)
- Quick Analysis
- SQL Syntax
- SQL Functions
- String Function
- Date and Time Functions
- IP Geographic Function
- URL Function
- Mathematical Calculation Functions
- Mathematical Statistical Function
- General Aggregate Function
- Geospatial Function
- Binary String Function
- Estimation Function
- Type Conversion Function
- Logical Function
- Operators
- Bitwise Operation
- Regular Expression Function
- Lambda Function
- Conditional Expressions
- Array Functions
- Interval-Valued Comparison and Periodicity-Valued Comparison Functions
- JSON Functions
- Window Functions
- Sampling Analysis
- Configuring Indexes
- Reindexing
- Context Search and Analysis
- Downloading Log
- Search and Analysis (Metric Topic)
- Dashboard
- Data Processing documents
- Data Processing
- Creating Processing Task
- Viewing Data Processing Details
- Data Processing Functions
- Function Overview
- Key-Value Extraction Functions
- Enrichment Functions
- Flow Control
- Row Processing Functions
- Field Processing Functions
- Value Structuring Functions
- Regular Expression Processing Functions
- Time Value Processing Functions
- String Processing Functions
- Type Conversion Functions
- Logical and Mathematical Functions
- Encoding and Decoding Functions
- IP Parsing Functions
- Processing Cases
- Scheduled SQL Analysis
- SCF
- Data Processing
- Shipping and Consumption
- Monitoring Alarm
- Historical Documentation
- Practical Tutorial
- Developer Guide
- API Documentation
- History
- Introduction
- API Category
- Making API Requests
- Topic Management APIs
- Log Set Management APIs
- Index APIs
- Topic Partition APIs
- Machine Group APIs
- Collection Configuration APIs
- Log APIs
- Metric APIs
- Alarm Policy APIs
- Data Processing APIs
- Kafka Protocol Consumption APIs
- CKafka Shipping Task APIs
- Kafka Data Subscription APIs
- COS Shipping Task APIs
- SCF Delivery Task APIs
- Scheduled SQL Analysis APIs
- COS Data Import Task APIs
- Data Types
- Error Codes
- FAQs
- CLS Service Level Agreement
- CLS Policy
- Contact Us
- Glossary
Using Separators to Extract Specified Content from Logs
Terakhir diperbarui:2024-01-20 17:44:35
Use Case
Tom has collected Flink task running logs to CLS in single-line text format. The log content is divided into segments with the comma (,) and colon (:) separators. Among these segments, there is a segment in escaped JSON format containing Flink task execution details. Tom wants to extract the task details and structure them.
Scenario Analysis
According to Tom's requirements, the processing ideas are as follows:
1. Extract the content in escaped JSON format.
2. Extract structured data from the JSON content.
Raw Log
{"regex": "2021-12-02 14:33:35.022 [1] INFO org.apache.Load - Response:status: 200, resp msg: OK, resp content: { \\"TxnId\\": 58322, \\"Label\\": \\"flink_connector_20211202_1de749d8c80015a8\\", \\"Status\\": \\"Success\\", \\"Message\\": \\"OK\\", \\"TotalRows\\": 1, \\"LoadedRows\\": 1, \\"FilteredRows\\": 0, \\"CommitAndPublishTimeMs\\": 16}"}
DSL Processing Function
ext_sepstr("regex", "f1, f2, f3", sep=",")fields_drop("regex")fields_drop("f1")fields_drop("f2")ext_sepstr("f3", "f1,resp_content", sep=":")fields_drop("f1")fields_drop("f3")ext_json("resp_content", prefix="")fields_drop("resp_content")
DSL Processing Function Details
1. Use commas (,) to divide the log into 3 segments, where the third segment f3 is resp content:{JSON}.
ext_sepstr("regex", "f1, f2, f3", sep=",")
2. Discard unwanted fields.
fields_drop("regex")fields_drop("f1")fields_drop("f2")
3. Use colons (:) to divide the f3 field into two segments.
ext_sepstr("f3", "f1,resp_content", sep=":")
4. Discard useless fields.
fields_drop("f1")fields_drop("f3")
5. Use the ext_json function to extract structured data from the resp_content field.
ext_json("resp_content", prefix="")
6. Discard the resp_content field.
fields_drop("resp_content")
Processing Result
{"CommitAndPublishTimeMs":"16","FilteredRows":"0","Label":"flink_connector_20211202_1de749d8c80015a8","LoadedRows":"1","Message":"OK","Status":"Success","TotalRows":"1","TxnId":"58322"}
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