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Table of Contents

Goals:

  1. Improve Metadata Search: This requires redesign of how we store metadata. Design proposed below.
    • Fix the bug in Metadata Search Make search for tags which works only work for all the first entry and not other tags in the list
    • Support tokenized search where user can search with any word from the value
  2. Schema Search:
    • CDAP Schema for Datasets, Streams and Views should be stored as metadata and searchable through fieldnames.
    Metadata Search Results:
  3. Jira Legacy
    serverCask Community Issue Tracker
    serverId45b48dee-c8d6-34f0-9990-e6367dc2fe4b
    keyCDAP-4274
    4. In addition to the above we will also like to return some other relevant info. Please see details below.
  4. Minor: We will also take Bhoosan's work on System Metadata to completion.
    • fieldname or and fieldname with fieldtype (only for primitive fieldtype)
  6. Search filtering based on entity type.

Checklist

  •  User stories documented (Rohit/Poorna)
  •  User stories reviewed (Nitin)
  •  Design documented (Rohit/Poorna)
  •  Design reviewed (Andreas)
  •  Feature merged (Rohit)
  •  Examples and guides (Rohit)
  •  Integration tests (Rohit) 
  •  Documentation for feature (Rohit)
  •  Blog post 

User Stories: 

...

  1. Key Value Metadata Search
    1. User should be able to search with key-
    value metadata with the following or with its prefix:
  2. key-value 
  3. key with part of value
  4. value
    5. Individual words in the value
    Example
    1. value or its prefix
    2. User should be able to search with key and individual word in value or its prefix
    3. User should be able to search with just value or its prefix
    4. User should be able to search with individual words in the value 
  5. Tag Metadata Search
    1. User should be able to search with tags key and a tag value or its prefix
    2. User should be able to search with just a tag value or its prefix.
  6. Schema Search:
    1. User should be able search with fieldname or its prefix
    2. User should be able to search with fieldname or its prefix scoped just to schema 
    3. User should be able to search with fieldname and fieldtype (only for primitive types)
  7. Search Filtering:
    1. User should be able to filter searches to a particular entity type for example app, program, dataset
  8. Partial Searching:
    1. User should be able to see result for individual words in search query.

Design

Search Query Examples:

  1. User stores a key-value metadata with key = "Codename" and value = "Alpha Tango Charlie" for an entity
    1. User
    should be able to search for
    1. can retrieve this entity with the following queries:
      • key-value
        1. Codename: Alpha Tango Charlie
        2. Codename: Alpha Tang*
      • key with part of value
        1. Codename: Alpha
        2. Codename: Tango
        3. Codename: Charlie
        4. Codename: Alp*
      • value
        1. Alpha Tango Charlie
        2. Alpha*
        3. Alpha Tan*
          Note:
          1. We have decided not to support searches for queries which have parts of value for example "Tango Charlie". You can either search for whole value or with prefix or single words (we plan to tokenize on whitespace) 
    parts of
      • Individual word in value
        1. Alpha
        2. Tango
        3. Charlie
        4. Alph*
        5. Tan*
        6. Ch*
    User should be able to search tags metadata with the following or with its prefix
    1. Not supported:
      1. tags key and a tag value
        2. a tag value
        Example:
          1. key* i.e. Codename*
      2. User tags an entity with the following tags "Tag1, Tag22"
        • User should be able to search for can retrieve this entity with the following queries:
          • tag key and a tag value:
            1. tags: Tag1
            2. tags: Tag*
          • a tag value
            1. tag22 
            2. tag2*
        User should be able search for entities (datasets, streams, views) through field-names in schema with the following or with its prefix:
      3. fieldname
        4. fieldname scoped with schema - this should limit the search to just schema fields and not other metadata
        User should be able to search for all entities with which has a schema
        Example:

      4. A dataset has the following schema: 

        Code Block
        titleNested Schema
        {
  "EmpName": "String",
  "EmpContact": {
    "EmpTel": "Integer",
    "EmpAddr": "String"
  }
}

        User

        should be able to search for

        can retrieve this dataset entity with the following queries:

        • fieldname:
          1. EmpName
          2. EmpContact
          3. EmpTel 
          4. EmpAddr
          5. Emp*
        • fieldname scoped to schema:
          1. schema: EmpName
          2. schema: EmpContact
          3. schema: EmpTel
          4. schema: EmpAddr 
          5. schema: Emp*
        search for all entities with a schemaschema:* This will return this dataset entity and also all the other entities which have schema stored as their metadata
        • fieldname with fieldtype (only for primitive types)
          1. EmpName:String (only for java primitive types)

        Note:
        1. We don't plan to support schema searches with complex fieldType. If a user  searched with a query which is not scoped with schema by default it will search for schema fields besides the normal key-value and tags.
          Open questions:
          • What if an entity has multiple schema (ex: transform which has input and output schema)
            • Maybe We can index its fields with input and output schema and we expect an user to specify whether they are looking for something in input schema or output schema. What about entities which have more than one schema?Maybe we can store them either as input output with identifier.will index both schema (After discussion with Nitin)
          • How will an user search for a fieldName across input and output schema ?
            • One way is to besides indexing the fields as input and output schema we also index every field as just schema so that we can perform such queries.

       Goal 3:

      ...

      Search Result:

      ...

      Metadata search will return Entities with the following details depending upon the type of the Entity.

       

      ...

      Type

      ...

       

       

      ...

      Design Decision:

      ...

      • In the search result of entity we will return all the metadata for that entity too. 

      ...

      • Please suggest other things which we can add to different search result entities ? 

       

      ...

            • We do not support searches limited to input/output or just one schema (After discussion with Nitin)
      2. Search Filtering:
        1. User wants to search only for 'dataset'
          1. dataset: Codename: Alpha
          2. dataset: tags: Tag1
          3. dataset: schema: EmpName
            Note: if not entity type is specified we will return all matched entities. 
      3. Partial Searching:
        1. User searches for  "California USA" : Separate every search query on white space and search for every single word (or)
          Search result will contain:
          1. All entities tagged with  "California USA" followed by
          2. All entities tagged with "California" followed by
          3. All entities tagged with "USA"

      Storage:

      We are going to use the IndexedTable which we are using currently too. In the new storage design we will have two rows: 

      1. Value Row: This row will store the entity id with key and value in the value column
      2. Index Row: This row will store the entity the entity id with key (like above) appended by the index which is also stored in the index column. The index column will be used for indexing.

       

      Metadata Storage Format:

      Key ColumnValue Column
      <VRPrefix><Entity-Id><Key>Value
      <VRPrefix><Entity<VRPrefix><Entity-Id><Tags>Tag1, Tag2, Tag3....
      <VRPrefix><Entity<VRPrefix><Entity-Id><Schema>{Some Schema}

      Index Storage Format:

      Key ColumnIndex Column
      <IRPrefix><Entity-Id><Key><Index>Index
      <IRPrefix><Entity<IRPrefix><Entity-Id><Tags><Index>Index
      <IRPrefix><Entity<IRPrefix><Entity-Id><Schema><Index>Index

       

      This table data represents key-value, tags and schema example discussed above to show how we plan to store the data. Index  Index Column contains all the possibilities of search queries. 

      Key: Entity with keyValue Column: Value of Metadata (Not Indexed)Index Column: Indexed value (Indexed)
      <VRPrefix><Entity-Id><CodeName>Alpha Tango Charlie 
      <VRPrefix><Entity-Id><Tags>Tag1, Tag22 
      <VRPrefix><Entity-Id><Schema>{EmpName: String, EmpContact: {EmpTel: Integer, EmpAddr: String}} 
      <IRPrefix><Entity-Id><Codename><CodeNameId><Codename><CodeName: Alpha Tango Charlie> CodeName: Alpha Tango Charlie
      <IRPrefix><Entity-Id><Codename><Codename<IRPrefix><Entity-Id><Codename><Codename: Alpha> Codename: Alpha
      <IRPrefix><Entity-Id><Codename><Codename<IRPrefix><Entity-Id><Codename><Codename: Tango> Codename: Tango
      <IRPrefix><Entity-Id><Codename><Codename<IRPrefix><Entity-Id><Codename><Codename: Charlie> Codename: Charlie
      <IRPrefix><Entity<IRPrefix><Entity-Id><Codename><Alpha Tango Charlie> Alpha Tango Charlie
      <IRPrefix><Entity-Id><Codename><Alpha><IRPrefix><Entity-Id><Codename><Alpha> Alpha
      <IRPrefix><Entity-Id><Codename><Tango><IRPrefix><Entity-Id><Codename><Tango> Tango
      <IRPrefix><Entity-Id><Codename><Charlie><IRPrefix><Entity-Id><Codename><Charlie> Charlie
      <IRPrefix><Entity<IRPrefix><Entity-Id><tags><tags: Tag1> tags: Tag1
      <IRPrefix><Entity-Id><tags><tags<IRPrefix><Entity-Id><tags><tags: Tag22> tags: Tag22
      <IRPrefix><Entity-Id><tags><Tag1><IRPrefix><Entity-Id><tags><Tag1> Tag1
      <IRPrefix><Entity-Id><tags><Tag22><IRPrefix><Entity-Id><tags><Tag22> Tag22
      <IRPrefix><Entity<IRPrefix><Entity-Id><schema><schema: EmpName> schema: EmpName
      <IRPrefix><Entity-Id><schema><schema<IRPrefix><Entity-Id><schema><schema: EmpContact> schema: EmpContact
      <IRPrefix><Entity-Id><schema><schema<IRPrefix><Entity-Id><schema><schema: EmpTel> schema: EmpTel
      <IRPrefix><Entity-Id><schema><schema<IRPrefix><Entity-Id><schema><schema: EmpAddr> schema: EmpAddr
      <IRPrefix><Entity-Id><schema><EmpName><IRPrefix><Entity-Id><schema><EmpName> EmpName
      <IRPrefix><Entity-Id><schema><EmpContact><IRPrefix><Entity-Id><schema><EmpContact> EmpContact
      <IRPrefix><Entity-Id><schema><EmpTel><IRPrefix><Entity-Id><schema><EmpTel> EmpTel
      <IRPrefix><Entity-Id><schema><EmpAddr><IRPrefix><Entity-Id><schema><EmpAddr> EmpAddr

      We will be using the indexedTable like before but now our keys which store values will be prefixed with a special VRPrefix (ValueRowPrefix) and we will store the value in the value column. The indexes will also be stored in the same table and the key will be prefixes with IRPrefix (IndexRowPrefix), the value column for such rows will be empty and the index column will have the index value which will be indexed for search.

      Another possibility was to store the real key value in a separate table and the indexes in the indexedTable which will avoid the empty column values for a row but this will lead to 6 tables on total (3 for system and business each) hence we have decided against it.

      Search Filtering: We will perform post filtering if the query is limited to an entity type. 

      In addition to above goals we also plan to do the following:

      1. Metadata Search Results:

        • Image AddedCDAP-4274 - Metadata search should returns the metadata of matching entities (Image Added Open)
        • Also return some other relevant info. Please see details below.

        Search Result 

        Metadata search will return Entities with the following details depending upon the type of the Entity. The search results will be order descending on basis of entity creation time.

      ...

      1. Entity TypeSearch Details
        Application

        Type

         Name
         Matched Metadata (Snippet) with all system metadata
         App Description
         Entity creation time
        ProgramType
         Name
         Matched Metadata (Snippet) with all system metadata
         App it belongs to
         Entity creation time
        ArtifactType
         Name
         Matched Metadata (Snippet) with all system metadata
         Entity creation time
        DatasetType
         Name
         Matched Metadata (Snippet) with all system metadata
         Entity creation time
        StreamName
         Type
         Matched Metadata (Snippet) with all system metadata
         Entity creation time
        ViewName



        		Type
        Matched Metadata (Snippet) with all system metadata
        Stream Name
        Entity creation time

        Design Decision: 

          • In the search result of entity we will return the matched metadata with all the system metadata for that entity too. 

        Open Question: 

          • Please suggest other things which we can add to different search result entities ? 

      2. Emit more metadata from system entities:

      Here is a list of System Metadata which we are planning to emit from different entities. If you have any suggestions as what other info can be useful as system metadata please comment below.

      Artifacts

        • Artifact name
        • Version

      Applications

        • Application name
        • ArtifactId
        • Plugins
          • Plugin Type
          • Plugin Name
        • Schedule
        • Programs

      Programs

        • Program name
        • Type: Flow, MapReduce etc
          • Workflow
          • Nodes under this workflow
        • Mode: Batch, Realtime

      Datasets

        • Dataset name
        • Schema
        • RecordScannable/BatchWritable/RecordWritable/BatchReadable
        • Type: KVTable, FileSet etc
        • ttl

      Streams

        • Stream name
        • Schema
        • ttl

      Views

        • View name
        • Schema

      Open Questions:

        • Please suggest other things which we can add to different system metadata entries
        • Nitin Motgi: Can we call "business metadata" "user metadata" and also the table which stores it userMetadata table rather than business to keep it consistent with other stuff  like metrics etc. 

       

      Additional Requirement and Notes:

      1. Invalidate just * query
      2. Support Pagination of search result in backend
      3. User entity creation time for ordering of search result
      4. Support searched with stemming (workflow/workflows) : Porter Stemming
      5. Support and (&) operation: Example search query - app:appname & program