Document indexing
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@ -104,12 +104,12 @@ For instance, here is a possible sequence of events:
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(node2, tdiscard2', (v4, t4)) ; tdiscard2' = t3
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(node2, tdiscard2', (v4, t4)) ; tdiscard2' = t3
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```
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```
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**Generic algorithm for handling insertions:** A certain node i handles the InsertItem and is responsible for the correctness of this procedure.
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**Generic algorithm for handling insertions:** A certain node n handles the InsertItem and is responsible for the correctness of this procedure.
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1. Lock the key (or the whole table?) at this node to prevent concurrent updates of the value that would mess things up
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1. Lock the key (or the whole table?) at this node to prevent concurrent updates of the value that would mess things up
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2. Read current set of values
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2. Read current set of values
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3. Generate a new timestamp that is larger than the largest timestamp for node i
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3. Generate a new timestamp that is larger than the largest timestamp for node n
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4. Add the inserted value in the list of values of node i
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4. Add the inserted value in the list of values of node n
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5. Update the discard times to be the times set in the context, and accordingly discard overwritten values
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5. Update the discard times to be the times set in the context, and accordingly discard overwritten values
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6. Release lock
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6. Release lock
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7. Propagate updated value to other nodes
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7. Propagate updated value to other nodes
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@ -136,7 +136,28 @@ that keeps tracks of the number of triples stored for each partition key.
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This allows easy listing of all of the partition keys for which triples exist
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This allows easy listing of all of the partition keys for which triples exist
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in a bucket, as the partition key becomes the sort key in the index.
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in a bucket, as the partition key becomes the sort key in the index.
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TODO: writeup asynchronous counting strategy
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How indexing works:
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- Each node keeps a local count of how many items it stores for each partition,
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in a local Sled tree that is updated atomically when an item is modified.
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- These local counters are asynchronously stored in the index table which is
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a regular Garage table spread in the network. Counters are stored as LWW values,
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so basically the final table will have the following structure:
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```
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- pk: bucket
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- sk: partition key for which we are counting
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- v: lwwmap (node id -> number of items)
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```
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The final number of items present in the partition can be estimated by taking
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the maximum of the values (i.e. the value for the node that announces having
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the most items for that partition). In most cases the values for different node
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IDs should all be the same; more precisely, three node IDs should map to the
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same non-zero value, and all other node IDs that are present are tombstones
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that map to zeroes. Note that we need to filter out values from nodes that are
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no longer part of the cluster layout, as when nodes are removed they won't
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necessarily have had the time to set their counters to zero.
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## API Endpoints
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## API Endpoints
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