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Stream Ingestion with CLP

Support for encoding fields with CLP during ingestion.
This is an experimental feature. Configuration options and usage may change frequently until it is stabilized.
When performing stream ingestion of JSON records using Kafka, users can encode specific fields with CLP by using a CLP-specific StreamMessageDecoder.
CLP is a compressor designed to encode unstructured log messages in a way that makes them more compressible while retaining the ability to search them. It does this by decomposing the message into three fields:
  • the message's static text, called a log type;
  • repetitive variable values, called dictionary variables; and
  • non-repetitive variable values (called encoded variables since we encode them specially if possible).
Searches are similarly decomposed into queries on the individual fields.
Although CLP is designed for log messages, other unstructured text like file paths may also benefit from its encoding.
For example, consider this JSON record:
{
"timestamp": 1672531200000,
"message": "INFO Task task_12 assigned to container: [ContainerID:container_15], operation took 0.335 seconds. 8 tasks remaining.",
"logPath": "/mnt/data/application_123/container_15/stdout"
}
If the user specifies the fields message and logPath should be encoded with CLP, then the StreamMessageDecoder will output:
{
"timestamp": 1672531200000,
"message_logtype": "INFO Task \\x12 assigned to container: [ContainerID:\\x12], operation took \\x13 seconds. \\x11 tasks remaining.",
"message_dictionaryVars": [
"task_12",
"container_15"
],
"message_encodedVars": [
1801439850948198735,
8
],
"logPath_logtype": "/mnt/data/\\x12/\\x12/stdout",
"logPath_dictionaryVars": [
"application_123",
"container_15"
],
"logPath_encodedVars": []
}
In the fields with the _logtype suffix, \x11 is a placeholder for an integer variable, \x12 is a placeholder for a dictionary variable, and \x13 is a placeholder for a float variable. In message_encoedVars, the float variable 0.335 is encoded as an integer using CLP's custom encoding.
All remaining fields are processed in the same way as they are in org.apache.pinot.plugin.inputformat.json.JSONRecordExtractor. Specifically, fields in the table's schema are extracted from each record and any remaining fields are dropped.

Configuration

Table Index

Assuming the user wants to encode message and logPath as in the example, they should change/add the following settings to their tableIndexConfig (we omit irrelevant settings for brevity):
{
"tableIndexConfig": {
"streamConfigs": {
"stream.kafka.decoder.class.name": "org.apache.pinot.plugin.inputformat.clplog.CLPLogMessageDecoder",
"stream.kafka.decoder.prop.fieldsForClpEncoding": "message,logPath"
},
"varLengthDictionaryColumns": [
"message_logtype",
"message_dictionaryVars",
"logPath_logtype",
"logPath_dictionaryVars"
]
}
}
  • stream.kafka.decoder.prop.fieldsForClpEncoding is a comma-separated list of names for fields that should be encoded with CLP.
  • We use variable-length dictionaries for the logtype and dictionary variables since their length can vary significantly.
  • Ideally, we would disable the dictionaries for the encoded variable columns (since they are likely to be random), but currently, a bug prevents us from doing that for multi-valued number-type columns.

Schema

For the table's schema, users should configure the CLP-encoded fields as follows (we omit irrelevant settings for brevity):
{
"dimensionFieldSpecs": [
{
"name": "message_logtype",
"dataType": "STRING",
"maxLength": 2147483647
},
{
"name": "message_encodedVars",
"dataType": "LONG",
"singleValueField": false
},
{
"name": "message_dictionaryVars",
"dataType": "STRING",
"maxLength": 2147483647,
"singleValueField": false
},
{
"name": "message_logtype",
"dataType": "STRING",
"maxLength": 2147483647
},
{
"name": "message_encodedVars",
"dataType": "LONG",
"singleValueField": false
},
{
"name": "message_dictionaryVars",
"dataType": "STRING",
"maxLength": 2147483647,
"singleValueField": false
}
]
}
  • We use the maximum possible length for the logtype and dictionary variable columns.
  • The dictionary and encoded variable columns are multi-valued columns.

Searching and decoding CLP-encoded fields

There is currently no built-in support within Pinot for searching and decoding CLP-encoded fields. This will be added in future commits, potentially as a set of UDFs. The development of these features is being tracked in this design doc.