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https://issues.apache.org/jira/browse/LUCENE-1458?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12650585#action_12650585
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Marvin Humphrey commented on LUCENE-1458:
-----------------------------------------

> I think you "just" have to have "index version data" that's
> collectively read/written, atomically, and is then used to init all
> the components. This is what segments_N is in Lucene (and I think
> "Schema" is in KS/Lucy?): it contains all details that all
> sub-components need.

The equivalent to segments_N in KinoSearch is snapshot_N.meta, which is
encoded as JSON.  There's a KinoSearch::Index::Snapshot class that's
responsible for reading/writing it.

KinoSearch::Schema is for defining your index: global field properties,
default Analyzer, etc.  It's similar to Solr's schema.xml, but implemented as
an abstract class that users are required to subclass.  Translated to Java,
the subclassing might look something like this:

{code}
  class MySchema extends Schema {
    class URLField extends TextField {
        boolean analyzed() { return false; }
        boolean indexed() { return false; }
    }

    void initFields() {
      addField("title", "text");
      addField("content", "text");
      addField("url", new URLField());
    }

    Analyzer analyzer() {
      return new PolyAnalyzer("en");
    }
  }
{code}

I anticipate that Lucy will adopt both Schema and Snapshot in some form, but
after discussion.  

> If init'ing each sub-component is then costly (opening files,
> slurping things in, etc.) its OK because they are all still loading a
> consistent commit point.

So, something like this prospective Lucy code? (Lucy with Java bindings, that 
is.)

{code}
  MySchema schema = new MySchema();
  Snapshot snapshot = new Snapshot((Schema)schema);
  snapShot.readSnapShot("/path/to/index");
  MyTermsDictReader termsDictReader = new MyTermsDictReader(schema, snapshot);
  IndexReader reader = new IndexReader(schema, snapshot, null, null,
                                       (TermsDictReader)termsDictReader);
{code}

What if index files get deleted out from under that code block?  The user will
have to implement retry logic.


> Further steps towards flexible indexing
> ---------------------------------------
>
>                 Key: LUCENE-1458
>                 URL: https://issues.apache.org/jira/browse/LUCENE-1458
>             Project: Lucene - Java
>          Issue Type: New Feature
>          Components: Index
>    Affects Versions: 2.9
>            Reporter: Michael McCandless
>            Assignee: Michael McCandless
>            Priority: Minor
>             Fix For: 2.9
>
>         Attachments: LUCENE-1458.patch, LUCENE-1458.patch, LUCENE-1458.patch, 
> LUCENE-1458.patch
>
>
> I attached a very rough checkpoint of my current patch, to get early
> feedback.  All tests pass, though back compat tests don't pass due to
> changes to package-private APIs plus certain bugs in tests that
> happened to work (eg call TermPostions.nextPosition() too many times,
> which the new API asserts against).
> [Aside: I think, when we commit changes to package-private APIs such
> that back-compat tests don't pass, we could go back, make a branch on
> the back-compat tag, commit changes to the tests to use the new
> package private APIs on that branch, then fix nightly build to use the
> tip of that branch?o]
> There's still plenty to do before this is committable! This is a
> rather large change:
>   * Switches to a new more efficient terms dict format.  This still
>     uses tii/tis files, but the tii only stores term & long offset
>     (not a TermInfo).  At seek points, tis encodes term & freq/prox
>     offsets absolutely instead of with deltas delta.  Also, tis/tii
>     are structured by field, so we don't have to record field number
>     in every term.
> .
>     On first 1 M docs of Wikipedia, tii file is 36% smaller (0.99 MB
>     -> 0.64 MB) and tis file is 9% smaller (75.5 MB -> 68.5 MB).
> .
>     RAM usage when loading terms dict index is significantly less
>     since we only load an array of offsets and an array of String (no
>     more TermInfo array).  It should be faster to init too.
> .
>     This part is basically done.
>   * Introduces modular reader codec that strongly decouples terms dict
>     from docs/positions readers.  EG there is no more TermInfo used
>     when reading the new format.
> .
>     There's nice symmetry now between reading & writing in the codec
>     chain -- the current docs/prox format is captured in:
> {code}
> FormatPostingsTermsDictWriter/Reader
> FormatPostingsDocsWriter/Reader (.frq file) and
> FormatPostingsPositionsWriter/Reader (.prx file).
> {code}
>     This part is basically done.
>   * Introduces a new "flex" API for iterating through the fields,
>     terms, docs and positions:
> {code}
> FieldProducer -> TermsEnum -> DocsEnum -> PostingsEnum
> {code}
>     This replaces TermEnum/Docs/Positions.  SegmentReader emulates the
>     old API on top of the new API to keep back-compat.
>     
> Next steps:
>   * Plug in new codecs (pulsing, pfor) to exercise the modularity /
>     fix any hidden assumptions.
>   * Expose new API out of IndexReader, deprecate old API but emulate
>     old API on top of new one, switch all core/contrib users to the
>     new API.
>   * Maybe switch to AttributeSources as the base class for TermsEnum,
>     DocsEnum, PostingsEnum -- this would give readers API flexibility
>     (not just index-file-format flexibility).  EG if someone wanted
>     to store payload at the term-doc level instead of
>     term-doc-position level, you could just add a new attribute.
>   * Test performance & iterate.

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