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    1. USMartin Hock
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    1. COA Huffman tree is the first thing I wrote after I saw the chunks in the trie - I was thinking of trying to encode lines as bit strings, one string for each chunk, concatenated - but while I was writing the bit-packing logic, I thought about using flat value-typed arrays for the trie encoding instead. Implementing Huffman encoding correctly and efficiently, and decoding in particular, gets pretty tedious pretty quickly. I may pick it back up and perhaps encode based on character frequency instead.
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      1. USBarry Kelly
    2. COYes, indexing using less bits than 32 is something I've thought about. Other things: 16M character data is cutting close for 24 bits, but if I aligned character data to word boundaries, costing on average 0.5 bytes per chunk, I could use 24 bits to index up to 32M position, for half the saving. And that bit-packing logic I was writing for the Huffman tree encoding, may come in useful for using less than a whole number of bytes for storing indexes. My next step will probably be writing a "bitfield array" class.
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    3. COI'll award this one the win. I wrote up a bit-packed array class that can index signed or unsigned integers of constant bit width, and I determine the maximum width required when converting from my mutable loading-time StringTrie to my immutable SlimTrie. Storing the SlimTrie on disk and reloading later saves time and memory, avoiding stale GC garbage hanging around. Now down to 75M!
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Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

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