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construct/include/ircd/db
2017-09-08 03:47:52 -07:00
..
cell.h ircd::db: Improve seek() interface suite. 2017-09-08 03:47:49 -07:00
column.h ircd::db: Improve opts, snapshot, and conversions for column::iterator. 2017-09-08 03:47:51 -07:00
cursor.h ircd::db: Add preliminary cursor and where clause query. 2017-09-08 03:47:52 -07:00
database.h ircd::db: Support prefix indexing. 2017-09-08 03:47:50 -07:00
delta.h ircd::db: Allow empty delta value with default argument param. 2017-09-08 03:47:51 -07:00
index.h ircd::db: Add index interface. 2017-09-08 03:47:52 -07:00
opts.h ircd::db: Support prefix indexing. 2017-09-08 03:47:50 -07:00
README.md fixup! ircd::db: Develop object-store out of db system. 2017-03-30 18:18:28 -07:00
row.h ircd::db: Add preliminary tuple specific interface. 2017-09-08 03:47:52 -07:00
tuple.h ircd::db: Add preliminary tuple specific interface. 2017-09-08 03:47:52 -07:00
value.h ircd: Employ namespace scope extensions from c++1z/gnu++14. 2017-09-08 03:47:46 -07:00
where.h ircd::db: Add preliminary cursor and where clause query. 2017-09-08 03:47:52 -07:00

IRCd Database

IRCd's database is presented here primarily as a persistent Object store. In other words, the structure presented by the database can be represented with JSON. This is built from the primitives of column, row and cell.

Columns

While a simple key-value store could naively store a JSON document as a textual value, we provide additional structure schematized before opening a database: Every member of a JSON object is a column in this database. To address members within nested objects, we specify a column with a "foo.bar.baz" path syntax. This puts all columns at the same level in our code, even though they may represent deeply nested values.

Rows

Since columns are technically independent key-value stores (they have their own index), when an index key is the same between columns we call this a row. For basic object storage the schema is such that we use the same keys between all columns. For example, an index would be a username in a user database. The user database itself takes the form of a single JSON object and any member lookup happens on a user's row.

Cells

A cell is a single value in a column indexed by a key that should be able to form a row between columns. Consider the following near-json expression:

users["root"] = {"password", "foobar"};

In the users database, we find the column "password" and the row for "root" and set that cell to "foobar"

Consider these expressions for objects at some depth:

users["root"] = {"password.plaintext", "foobar"};
users["root"] = {"password", {"plaintext, "foobar"}};

The column is always found as "password.plaintext". We find it (and can iterate its members if it were an object) by string-manipulating these full paths which all sit in a single map and are always open, even if the cell is empty for some row.

Important notes

!!! The database system is plugged into the userspace context system to facilitate IO. This means that an expensive database call (mostly on the read side) that has to do disk IO will suspend your userspace context. Remember that when your userspace context resumes on the other side of the call, the state of IRCd and even the database itself may have changed. We have a suite of tools to mitigate this. !!!

  • While the database schema is modifiable at runtime (we can add and remove columns on the fly) the database is very picky about opening the exact same way it last closed. This means, for now, we have the full object schema explicitly specified when the DB is first opened. All columns exist for the lifetime of the DB, whether or not you have a handle to them.