mentat/db/src/tx.rs
Nick Alexander 5369f03464 Improve parsing of nested edn::ValueAndSpan streams. r=rnewman (#393)
* Pre: Expose more in edn.

* Pre: Make it easier to work with ValueAndSpan.

with_spans() is a temporary hack, needed only because I don't care to
parse the bootstrap assertions from text right now.

* Part 1a: Add `value_and_span` for parsing nested `edn::ValueAndSpan` instances.

I wasn't able to abstract over `edn::Value` and `edn::ValueAndSpan`;
there are multiple obstacles.  I chose to roll with
`edn::ValueAndSpan` since it exposes the additional span information
that we will want to form good error messages in the future.

* Part 1b: Add keyword_map() parsing an `edn::Value::Vector` into an `edn::Value::map`.

* Part 1c: Add `Log`/`.log(...)` for logging parser progress.

This is a terrible hack, but it sure helps to debug complicated nested
parsers.  I don't even know what a principled approach would look
like; since our parser combinators are so frequently expressed in
code, it's hard to imagine a data-driven interpreter that can help
debug things.

* Part 2: Use `value_and_span` apparatus in tx-parser/.

I break an abstraction boundary by returning a value column
`edn::ValueAndSpan` rather than just an `edn::Value`.  That is, the
transaction processor shouldn't care where the `edn::Value` it is
processing arose -- even we care to track that information we should
bake it into the `Entity` type.  We do this because we need to
dynamically parse the value column to support nested maps, and parsing
requires a full `edn::ValueAndSpan`.  Alternately, we could cheat and
fake the spans when parsing nested maps, but that's potentially
expensive.

* Part 3: Use `value_and_span` apparatus in query-parser/.

* Part 4: Use `value_and_span` apparatus in root crate.

* Review comment: Make Span and SpanPosition Copy.

* Review comment: nits.

* Review comment: Make `or` be `or_exactly`.

I baked the eof checking directly into the parser, rather than using
the skip and eof parsers.  I also took the time to restore some tests
that were mistakenly commented out.

* Review comment: Extract and use def_matches_* macros.

* Review comment: .map() as late as possible.
2017-04-06 10:06:28 -07:00

615 lines
30 KiB
Rust

// Copyright 2016 Mozilla
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use
// this file except in compliance with the License. You may obtain a copy of the
// License at http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
#![allow(dead_code)]
//! This module implements the transaction application algorithm described at
//! https://github.com/mozilla/mentat/wiki/Transacting and its children pages.
//!
//! The implementation proceeds in four main stages, labeled "Pipeline stage 1" through "Pipeline
//! stage 4". _Pipeline_ may be a misnomer, since the stages as written **cannot** be interleaved
//! in parallel. That is, a single transacted entity cannot flow through all the stages without its
//! sibling entities.
//!
//! This unintuitive architectural decision was made because the second and third stages (resolving
//! lookup refs and tempids, respectively) operate _in bulk_ to minimize the number of expensive
//! SQLite queries by processing many in one SQLite invocation. Pipeline stage 2 doesn't need to
//! operate like this: it is easy to handle each transacted entity independently of all the others
//! (and earlier, less efficient, implementations did this). However, Pipeline stage 3 appears to
//! require processing multiple elements at the same time, since there can be arbitrarily complex
//! graph relationships between tempids. Pipeline stage 4 (inserting elements into the SQL store)
//! could also be expressed as an independent operation per transacted entity, but there are
//! non-trivial uniqueness relationships inside a single transaction that need to enforced.
//! Therefore, some multi-entity processing is required, and a per-entity pipeline becomes less
//! attractive.
//!
//! A note on the types in the implementation. The pipeline stages are strongly typed: each stage
//! accepts and produces a subset of the previous. We hope this will reduce errors as data moves
//! through the system. In contrast the Clojure implementation rewrote the fundamental entity type
//! in place and suffered bugs where particular code paths missed cases.
//!
//! The type hierarchy accepts `Entity` instances from the transaction parser and flows `Term`
//! instances through the term-rewriting transaction applier. `Term` is a general `[:db/add e a v]`
//! with restrictions on the `e` and `v` components. The hierarchy is expressed using `Result` to
//! model either/or, and layers of `Result` are stripped -- we might say the `Term` instances are
//! _lowered_ as they flow through the pipeline. This type hierarchy could have been expressed by
//! combinatorially increasing `enum` cases, but this makes it difficult to handle the `e` and `v`
//! components symmetrically. Hence, layers of `Result` type aliases. Hopefully the explanatory
//! names -- `TermWithTempIdsAndLookupRefs`, anyone? -- and strongly typed stage functions will help
//! keep everything straight.
use std::borrow::Cow;
use std::collections::{
BTreeMap,
BTreeSet,
VecDeque,
};
use db;
use db::{
MentatStoring,
PartitionMapping,
};
use entids;
use errors::{ErrorKind, Result};
use internal_types::{
Either,
LookupRef,
LookupRefOrTempId,
TempIdHandle,
TempIdMap,
Term,
TermWithTempIdsAndLookupRefs,
TermWithTempIds,
TermWithoutTempIds,
replace_lookup_ref};
use mentat_core::{
attribute,
intern_set,
Schema,
};
use mentat_tx::entities as entmod;
use mentat_tx::entities::{
Entity,
OpType,
TempId,
};
use mentat_tx_parser;
use metadata;
use rusqlite;
use schema::{
SchemaBuilding,
SchemaTypeChecking,
};
use types::{
Attribute,
AVPair,
AVMap,
Entid,
PartitionMap,
TypedValue,
TxReport,
ValueType,
};
use upsert_resolution::Generation;
/// A transaction on its way to being applied.
#[derive(Debug)]
pub struct Tx<'conn, 'a> {
/// The storage to apply against. In the future, this will be a Mentat connection.
store: &'conn rusqlite::Connection, // TODO: db::MentatStoring,
/// The partition map to allocate entids from.
///
/// The partition map is volatile in the sense that every succesful transaction updates
/// allocates at least one tx ID, so we own and modify our own partition map.
partition_map: PartitionMap,
/// The schema to update from the transaction entities.
///
/// Transactions only update the schema infrequently, so we borrow this schema until we need to
/// modify it.
schema_for_mutation: Cow<'a, Schema>,
/// The schema to use when interpreting the transaction entities.
///
/// This schema is not updated, so we just borrow it.
schema: &'a Schema,
/// The transaction ID of the transaction.
tx_id: Entid,
/// The timestamp when the transaction began to be committed.
///
/// This is milliseconds after the Unix epoch according to the transactor's local clock.
// TODO: :db.type/instant.
tx_instant: i64,
}
impl<'conn, 'a> Tx<'conn, 'a> {
pub fn new(
store: &'conn rusqlite::Connection,
partition_map: PartitionMap,
schema_for_mutation: &'a Schema,
schema: &'a Schema,
tx_id: Entid,
tx_instant: i64) -> Tx<'conn, 'a> {
Tx {
store: store,
partition_map: partition_map,
schema_for_mutation: Cow::Borrowed(schema_for_mutation),
schema: schema,
tx_id: tx_id,
tx_instant: tx_instant,
}
}
/// Given a collection of tempids and the [a v] pairs that they might upsert to, resolve exactly
/// which [a v] pairs do upsert to entids, and map each tempid that upserts to the upserted
/// entid. The keys of the resulting map are exactly those tempids that upserted.
pub fn resolve_temp_id_avs<'b>(&self, temp_id_avs: &'b [(TempIdHandle, AVPair)]) -> Result<TempIdMap> {
if temp_id_avs.is_empty() {
return Ok(TempIdMap::default());
}
// Map [a v]->entid.
let mut av_pairs: Vec<&AVPair> = vec![];
for i in 0..temp_id_avs.len() {
av_pairs.push(&temp_id_avs[i].1);
}
// Lookup in the store.
let av_map: AVMap = self.store.resolve_avs(&av_pairs[..])?;
// Map id->entid.
let mut temp_id_map: TempIdMap = TempIdMap::default();
for &(ref temp_id, ref av_pair) in temp_id_avs {
if let Some(n) = av_map.get(&av_pair) {
if let Some(previous_n) = temp_id_map.get(&*temp_id) {
if n != previous_n {
// Conflicting upsert! TODO: collect conflicts and give more details on what failed this transaction.
bail!(ErrorKind::NotYetImplemented(format!("Conflicting upsert: tempid '{}' resolves to more than one entid: {:?}, {:?}", temp_id, previous_n, n))) // XXX
}
}
temp_id_map.insert(temp_id.clone(), *n);
}
}
Ok((temp_id_map))
}
/// Pipeline stage 1: convert `Entity` instances into `Term` instances, ready for term
/// rewriting.
///
/// The `Term` instances produce share interned TempId and LookupRef handles, and we return the
/// interned handle sets so that consumers can ensure all handles are used appropriately.
fn entities_into_terms_with_temp_ids_and_lookup_refs<I>(&self, entities: I) -> Result<(Vec<TermWithTempIdsAndLookupRefs>, intern_set::InternSet<TempId>, intern_set::InternSet<AVPair>)> where I: IntoIterator<Item=Entity> {
let mut temp_ids: intern_set::InternSet<TempId> = intern_set::InternSet::new();
let mut lookup_refs: intern_set::InternSet<AVPair> = intern_set::InternSet::new();
let intern_lookup_ref = |lookup_refs: &mut intern_set::InternSet<AVPair>, lookup_ref: entmod::LookupRef| -> Result<LookupRef> {
let lr_a: i64 = match lookup_ref.a {
entmod::Entid::Entid(ref a) => *a,
entmod::Entid::Ident(ref a) => self.schema.require_entid(&a)?,
};
let lr_attribute: &Attribute = self.schema.require_attribute_for_entid(lr_a)?;
if lr_attribute.unique.is_none() {
bail!(ErrorKind::NotYetImplemented(format!("Cannot resolve (lookup-ref {} {}) with attribute that is not :db/unique", lr_a, lookup_ref.v)))
}
let lr_typed_value: TypedValue = self.schema.to_typed_value(&lookup_ref.v, &lr_attribute)?;
Ok(lookup_refs.intern((lr_a, lr_typed_value)))
};
// We want to handle entities in the order they're given to us, while also "exploding" some
// entities into many. We therefore push the initial entities onto the back of the deque,
// take from the front of the deque, and explode onto the front as well.
let mut deque: VecDeque<Entity> = VecDeque::default();
deque.extend(entities);
// Allocate private internal tempids reserved for Mentat. Internal tempids just need to be
// unique within one transaction; they should never escape a transaction.
let mut mentat_id_count = 0;
let mut allocate_mentat_id = move || {
mentat_id_count += 1;
entmod::EntidOrLookupRefOrTempId::TempId(TempId::Internal(mentat_id_count))
};
let mut terms: Vec<TermWithTempIdsAndLookupRefs> = Vec::with_capacity(deque.len());
while let Some(entity) = deque.pop_front() {
match entity {
Entity::MapNotation(mut map_notation) => {
// :db/id is optional; if it's not given, we generate a special internal tempid
// to use for upserting. This tempid will not be reported in the TxReport.
let db_id: entmod::EntidOrLookupRefOrTempId = mentat_tx_parser::remove_db_id(&mut map_notation)?.unwrap_or_else(&mut allocate_mentat_id);
// We're not nested, so :db/isComponent is not relevant. We just explode the
// map notation.
for (a, v) in map_notation {
deque.push_front(Entity::AddOrRetract {
op: OpType::Add,
e: db_id.clone(),
a: a,
v: v,
});
}
},
Entity::AddOrRetract { op, e, a, v } => {
let a: i64 = match a {
entmod::Entid::Entid(ref a) => *a,
entmod::Entid::Ident(ref a) => self.schema.require_entid(&a)?,
};
let attribute: &Attribute = self.schema.require_attribute_for_entid(a)?;
let v = match v {
entmod::AtomOrLookupRefOrVectorOrMapNotation::Atom(v) => {
if attribute.value_type == ValueType::Ref && v.inner.is_text() {
Either::Right(LookupRefOrTempId::TempId(temp_ids.intern(v.inner.as_text().cloned().map(TempId::External).unwrap())))
} else {
// Here is where we do schema-aware typechecking: we either assert that
// the given value is in the attribute's value set, or (in limited
// cases) coerce the value into the attribute's value set.
let typed_value: TypedValue = self.schema.to_typed_value(&v.without_spans(), &attribute)?;
Either::Left(typed_value)
}
},
entmod::AtomOrLookupRefOrVectorOrMapNotation::LookupRef(lookup_ref) => {
if attribute.value_type != ValueType::Ref {
bail!(ErrorKind::NotYetImplemented(format!("Cannot resolve value lookup ref for attribute {} that is not :db/valueType :db.type/ref", a)))
}
Either::Right(LookupRefOrTempId::LookupRef(intern_lookup_ref(&mut lookup_refs, lookup_ref)?))
},
entmod::AtomOrLookupRefOrVectorOrMapNotation::Vector(vs) => {
if !attribute.multival {
bail!(ErrorKind::NotYetImplemented(format!("Cannot explode vector value for attribute {} that is not :db.cardinality :db.cardinality/many", a)));
}
for vv in vs {
deque.push_front(Entity::AddOrRetract {
op: op.clone(),
e: e.clone(),
a: entmod::Entid::Entid(a),
v: vv,
});
}
continue
},
entmod::AtomOrLookupRefOrVectorOrMapNotation::MapNotation(mut map_notation) => {
// TODO: consider handling this at the tx-parser level. That would be
// more strict and expressive, but it would lead to splitting
// AddOrRetract, which proliferates types and code, or only handling
// nested maps rather than map values, like Datomic does.
if op != OpType::Add {
bail!(ErrorKind::NotYetImplemented(format!("Cannot explode nested map value in :db/retract for attribute {}", a)));
}
if attribute.value_type != ValueType::Ref {
bail!(ErrorKind::NotYetImplemented(format!("Cannot explode nested map value for attribute {} that is not :db/valueType :db.type/ref", a)))
}
// :db/id is optional; if it's not given, we generate a special internal tempid
// to use for upserting. This tempid will not be reported in the TxReport.
let db_id: Option<entmod::EntidOrLookupRefOrTempId> = mentat_tx_parser::remove_db_id(&mut map_notation)?;
let mut dangling = db_id.is_none();
let db_id: entmod::EntidOrLookupRefOrTempId = db_id.unwrap_or_else(&mut allocate_mentat_id);
// We're nested, so we want to ensure we're not creating "dangling"
// entities that can't be reached. If we're :db/isComponent, then this
// is not dangling. Otherwise, the resulting map needs to have a
// :db/unique :db.unique/identity [a v] pair, so that it's reachable.
// Per http://docs.datomic.com/transactions.html: "Either the reference
// to the nested map must be a component attribute, or the nested map
// must include a unique attribute. This constraint prevents the
// accidental creation of easily-orphaned entities that have no identity
// or relation to other entities."
if attribute.component {
dangling = false;
}
for (inner_a, inner_v) in map_notation {
let inner_entid: i64 = match inner_a {
entmod::Entid::Entid(ref a) => *a,
entmod::Entid::Ident(ref a) => self.schema.require_entid(&a)?,
};
let inner_attribute: &Attribute = self.schema.require_attribute_for_entid(inner_entid)?;
if inner_attribute.unique == Some(attribute::Unique::Identity) {
dangling = false;
}
deque.push_front(Entity::AddOrRetract {
op: OpType::Add,
e: db_id.clone(),
a: entmod::Entid::Entid(inner_entid),
v: inner_v,
});
}
if dangling {
bail!(ErrorKind::NotYetImplemented(format!("Cannot explode nested map value that would lead to dangling entity for attribute {}", a)));
}
// Similar, but not identical, to the expansion of the entity position e
// below. This returns Either::Left(TypedValue) instances; that returns
// Either::Left(i64) instances.
match db_id {
entmod::EntidOrLookupRefOrTempId::Entid(e) => {
let e: i64 = match e {
entmod::Entid::Entid(ref e) => *e,
entmod::Entid::Ident(ref e) => self.schema.require_entid(&e)?,
};
Either::Left(TypedValue::Ref(e))
},
entmod::EntidOrLookupRefOrTempId::TempId(e) => {
Either::Right(LookupRefOrTempId::TempId(temp_ids.intern(e)))
},
entmod::EntidOrLookupRefOrTempId::LookupRef(lookup_ref) => {
Either::Right(LookupRefOrTempId::LookupRef(intern_lookup_ref(&mut lookup_refs, lookup_ref)?))
},
}
},
};
let e = match e {
entmod::EntidOrLookupRefOrTempId::Entid(e) => {
let e: i64 = match e {
entmod::Entid::Entid(ref e) => *e,
entmod::Entid::Ident(ref e) => self.schema.require_entid(&e)?,
};
Either::Left(e)
},
entmod::EntidOrLookupRefOrTempId::TempId(e) => {
Either::Right(LookupRefOrTempId::TempId(temp_ids.intern(e)))
},
entmod::EntidOrLookupRefOrTempId::LookupRef(lookup_ref) => {
Either::Right(LookupRefOrTempId::LookupRef(intern_lookup_ref(&mut lookup_refs, lookup_ref)?))
},
};
terms.push(Term::AddOrRetract(op, e, a, v));
},
}
};
Ok((terms, temp_ids, lookup_refs))
}
/// Pipeline stage 2: rewrite `Term` instances with lookup refs into `Term` instances without
/// lookup refs.
///
/// The `Term` instances produce share interned TempId handles and have no LookupRef references.
fn resolve_lookup_refs<I>(&self, lookup_ref_map: &AVMap, terms: I) -> Result<Vec<TermWithTempIds>> where I: IntoIterator<Item=TermWithTempIdsAndLookupRefs> {
terms.into_iter().map(|term: TermWithTempIdsAndLookupRefs| -> Result<TermWithTempIds> {
match term {
Term::AddOrRetract(op, e, a, v) => {
let e = replace_lookup_ref(&lookup_ref_map, e, |x| x)?;
let v = replace_lookup_ref(&lookup_ref_map, v, |x| TypedValue::Ref(x))?;
Ok(Term::AddOrRetract(op, e, a, v))
},
}
}).collect::<Result<Vec<_>>>()
}
/// Transact the given `entities` against the store.
///
/// This approach is explained in https://github.com/mozilla/mentat/wiki/Transacting.
// TODO: move this to the transactor layer.
pub fn transact_entities<I>(&mut self, entities: I) -> Result<TxReport> where I: IntoIterator<Item=Entity> {
// TODO: push these into an internal transaction report?
let mut tempids: BTreeMap<TempId, Entid> = BTreeMap::default();
// Pipeline stage 1: entities -> terms with tempids and lookup refs.
let (terms_with_temp_ids_and_lookup_refs, tempid_set, lookup_ref_set) = self.entities_into_terms_with_temp_ids_and_lookup_refs(entities)?;
// Pipeline stage 2: resolve lookup refs -> terms with tempids.
let lookup_ref_avs: Vec<&(i64, TypedValue)> = lookup_ref_set.inner.iter().map(|rc| &**rc).collect();
let lookup_ref_map: AVMap = self.store.resolve_avs(&lookup_ref_avs[..])?;
let terms_with_temp_ids = self.resolve_lookup_refs(&lookup_ref_map, terms_with_temp_ids_and_lookup_refs)?;
// Pipeline stage 3: upsert tempids -> terms without tempids or lookup refs.
// Now we can collect upsert populations.
let (mut generation, inert_terms) = Generation::from(terms_with_temp_ids, &self.schema)?;
// And evolve them forward.
while generation.can_evolve() {
// Evolve further.
let temp_id_map: TempIdMap = self.resolve_temp_id_avs(&generation.temp_id_avs()[..])?;
generation = generation.evolve_one_step(&temp_id_map);
// Report each tempid that resolves via upsert.
for (tempid, entid) in temp_id_map {
// Every tempid should be resolved at most once. Prima facie, we might expect a
// tempid to be resolved in two different generations. However, that is not so: the
// keys of temp_id_map are unique between generations.Suppose that id->e and id->e*
// are two such mappings, resolved on subsequent evolutionary steps, and that `id`
// is a key in the intersection of the two key sets. This can't happen: if `id` maps
// to `e` via id->e, all instances of `id` have been evolved forward (replaced with
// `e`) before we try to resolve the next set of `UpsertsE`. That is, we'll never
// successfully upsert the same tempid in more than one generation step. (We might
// upsert the same tempid to multiple entids via distinct `[a v]` pairs in a single
// generation step; in this case, the transaction will fail.)
let previous = tempids.insert((*tempid).clone(), entid);
assert!(previous.is_none());
}
}
// Allocate entids for tempids that didn't upsert. BTreeSet rather than HashSet so this is deterministic.
let unresolved_temp_ids: BTreeSet<TempIdHandle> = generation.temp_ids_in_allocations();
// TODO: track partitions for temporary IDs.
let entids = self.partition_map.allocate_entids(":db.part/user", unresolved_temp_ids.len());
let temp_id_allocations: TempIdMap = unresolved_temp_ids.into_iter().zip(entids).collect();
let final_populations = generation.into_final_populations(&temp_id_allocations)?;
// Report each tempid that is allocated.
for (tempid, &entid) in &temp_id_allocations {
// Every tempid should be allocated at most once.
assert!(!tempids.contains_key(&**tempid));
tempids.insert((**tempid).clone(), entid);
}
// Verify that every tempid we interned either resolved or has been allocated.
assert_eq!(tempids.len(), tempid_set.inner.len());
for tempid in &tempid_set.inner {
assert!(tempids.contains_key(&**tempid));
}
// Any internal tempid has been allocated by the system and is a private implementation
// detail; it shouldn't be exposed in the final transaction report.
let tempids = tempids.into_iter().filter_map(|(tempid, e)| tempid.into_external().map(|s| (s, e))).collect();
// A transaction might try to add or retract :db/ident assertions or other metadata mutating
// assertions , but those assertions might not make it to the store. If we see a possible
// metadata mutation, we will figure out if any assertions made it through later. This is
// strictly an optimization: it would be correct to _always_ check what made it to the
// store.
let mut tx_might_update_metadata = false;
let final_terms: Vec<TermWithoutTempIds> = [final_populations.resolved,
final_populations.allocated,
inert_terms.into_iter().map(|term| term.unwrap()).collect()].concat();
{ // TODO: Don't use this block to scope borrowing the schema; instead, extract a helper function.
/// Assertions that are :db.cardinality/one and not :db.fulltext.
let mut non_fts_one: Vec<db::ReducedEntity> = vec![];
/// Assertions that are :db.cardinality/many and not :db.fulltext.
let mut non_fts_many: Vec<db::ReducedEntity> = vec![];
/// Assertions that are :db.cardinality/one and :db.fulltext.
let mut fts_one: Vec<db::ReducedEntity> = vec![];
/// Assertions that are :db.cardinality/many and :db.fulltext.
let mut fts_many: Vec<db::ReducedEntity> = vec![];
// Pipeline stage 4: final terms (after rewriting) -> DB insertions.
// Collect into non_fts_*.
// TODO: use something like Clojure's group_by to do this.
for term in final_terms {
match term {
Term::AddOrRetract(op, e, a, v) => {
let attribute: &Attribute = self.schema.require_attribute_for_entid(a)?;
if entids::might_update_metadata(a) {
tx_might_update_metadata = true;
}
let added = op == OpType::Add;
let reduced = (e, a, attribute, v, added);
match (attribute.fulltext, attribute.multival) {
(false, true) => non_fts_many.push(reduced),
(false, false) => non_fts_one.push(reduced),
(true, false) => fts_one.push(reduced),
(true, true) => fts_many.push(reduced),
}
},
}
}
// Transact [:db/add :db/txInstant NOW :db/tx].
// TODO: allow this to be present in the transaction data.
non_fts_one.push((self.tx_id,
entids::DB_TX_INSTANT,
self.schema.require_attribute_for_entid(entids::DB_TX_INSTANT).unwrap(),
TypedValue::Long(self.tx_instant),
true));
if !non_fts_one.is_empty() {
self.store.insert_non_fts_searches(&non_fts_one[..], db::SearchType::Inexact)?;
}
if !non_fts_many.is_empty() {
self.store.insert_non_fts_searches(&non_fts_many[..], db::SearchType::Exact)?;
}
if !fts_one.is_empty() {
self.store.insert_fts_searches(&fts_one[..], db::SearchType::Inexact)?;
}
if !fts_many.is_empty() {
self.store.insert_fts_searches(&fts_many[..], db::SearchType::Exact)?;
}
self.store.commit_transaction(self.tx_id)?;
}
db::update_partition_map(self.store, &self.partition_map)?;
if tx_might_update_metadata {
// Extract changes to metadata from the store.
let metadata_assertions = self.store.committed_metadata_assertions(self.tx_id)?;
let mut new_schema = (*self.schema_for_mutation).clone(); // Clone the underlying Schema for modification.
let metadata_report = metadata::update_schema_from_entid_quadruples(&mut new_schema, metadata_assertions)?;
// We might not have made any changes to the schema, even though it looked like we
// would. This should not happen, even during bootstrapping: we mutate an empty
// `Schema` in this case specifically to run the bootstrapped assertions through the
// regular transactor code paths, updating the schema and materialized views uniformly.
// But, belt-and-braces: handle it gracefully.
if new_schema != *self.schema_for_mutation {
let old_schema = (*self.schema_for_mutation).clone(); // Clone the original Schema for comparison.
*self.schema_for_mutation.to_mut() = new_schema; // Store the new Schema.
db::update_metadata(self.store, &old_schema, &*self.schema_for_mutation, &metadata_report)?;
}
}
Ok(TxReport {
tx_id: self.tx_id,
tx_instant: self.tx_instant,
tempids: tempids,
})
}
}
/// Transact the given `entities` against the given SQLite `conn`, using the given metadata.
///
/// This approach is explained in https://github.com/mozilla/mentat/wiki/Transacting.
// TODO: move this to the transactor layer.
pub fn transact<'conn, 'a, I>(
conn: &'conn rusqlite::Connection,
mut partition_map: PartitionMap,
schema_for_mutation: &'a Schema,
schema: &'a Schema,
entities: I) -> Result<(TxReport, PartitionMap, Option<Schema>)> where I: IntoIterator<Item=Entity> {
// Eventually, this function will be responsible for managing a SQLite transaction. For
// now, it's just about the tx details.
let tx_instant = ::now(); // Label the transaction with the timestamp when we first see it: leading edge.
let tx_id = partition_map.allocate_entid(":db.part/tx");
conn.begin_transaction()?;
let mut tx = Tx::new(conn, partition_map, schema_for_mutation, schema, tx_id, tx_instant);
let report = tx.transact_entities(entities)?;
// If the schema has moved on, return it.
let next_schema = match tx.schema_for_mutation {
Cow::Borrowed(_) => None,
Cow::Owned(next_schema) => Some(next_schema),
};
Ok((report, tx.partition_map, next_schema))
}