feat: Add thread safe transactional in-memory datastore #947

fredcarle · 2022-11-16T23:44:02Z

Relevant issue(s)

Resolves #946

Description

This PR provides a thread safe in memory store that supports both ds.Batching and ds.TxnFeature. It uses a btree as storage.

Tasks

I made sure the code is well commented, particularly hard-to-understand areas.
I made sure the repository-held documentation is changed accordingly.
I made sure the pull request title adheres to the conventional commit style (the subset used in the project can be found in tools/configs/chglog/config.yml).
I made sure to discuss its limitations such as threats to validity, vulnerability to mistake and misuse, robustness to invalidation of assumptions, resource requirements, ...

How has this been tested?

make test

Specify the platform(s) on which this was tested:

MacOS

codecov · 2022-11-16T23:53:08Z

Codecov Report

Merging #947 (1f1b84b) into develop (0261377) will increase coverage by 0.64%.
The diff coverage is 89.24%.

@@             Coverage Diff             @@
##           develop     #947      +/-   ##
===========================================
+ Coverage    57.11%   57.75%   +0.64%     
===========================================
  Files          164      167       +3     
  Lines        19020    19408     +388     
===========================================
+ Hits         10863    11210     +347     
- Misses        7173     7204      +31     
- Partials       984      994      +10

Impacted Files	Coverage Δ
datastore/txn.go	`63.07% <71.42%> (-2.31%)`	⬇️
datastore/memory/memory.go	`88.73% <88.73%> (ø)`
datastore/memory/txn.go	`89.02% <89.02%> (ø)`
datastore/memory/batch.go	`100.00% <100.00%> (ø)`
db/fetcher/versioned.go	`52.87% <100.00%> (+0.52%)`	⬆️
connor/lt.go	`58.33% <0.00%> (-2.78%)`	⬇️
db/collection_update.go	`58.46% <0.00%> (-0.24%)`	⬇️
db/collection.go	`66.20% <0.00%> (-0.16%)`	⬇️

jsimnz

Overall, great implementation!!

There's some notable suggestions, and some minimal ones.

But looking great! Should be easy enough to resolve everything

jsimnz · 2022-11-17T09:11:09Z

datastore/memory/memory.go

+// NewStore constructs an empty Store.
+func NewStore() (d *Store) {
+	return &Store{
+		values: btree.NewMap[string, []byte](2),


question: I can't actually find any info/docs on the degree parameter of 2 in this NewMap call.

It represents the number of items and children a node will have. A degree of 2 means a node will have 1-3 items and 2-4 children.

What made you choose 2?

I would suggest exposing this param, as it sounds very use-case specific (can be done outside of the PR, but might be worth a ticket+todo now)

datastore/memory/memory.go

datastore/memory/memory_test.go

datastore/memory/txn.go

jsimnz · 2022-11-17T10:27:36Z

datastore/memory/txn.go

+	for k, v := range t.ops {
+		if _, handled := handledOps[k]; handled {
+			continue
+		}
+
+		if v.delete {
+			continue
+		}
+		e := dsq.Entry{Key: k.String(), Size: len(v.value)}
+		if !q.KeysOnly {
+			e.Value = v.value
+		}
+		re = append(re, e)
+	}


suggestion: Appending the ops entries to the results slice re will produce an un-ordered slice. Specifically, it will produce one ordered slice with extra unordered elements.

There's a few options here.

We leave it as is, but need to ensure that within NaiveQueryApply we make sure that NaiveOrder is executing properly. As the name suggests, it will effectively do a sort on the results, then pass it along.
This is likely exactly whats happening now, but its pretty in-effecient, ideally should be avoided

We insert "in-order" in this function here, but that might be awkward as it will require a bunch of scans to find the insert position since we're insert records from an unordered map into an ordered slice.

We merge the re values slice, with a new sorted slice from the ops map. Then its just merging two sorted arrays which is pretty easy (similar to the Mergeiterator design below)

Looking at how Badger does this, it effectively produces two iterators, one for values and another for ops. Then it combines them into a MergeIterator, which will consume both iterators, returning the smaller of the two values returned from the two individual iterators.

Iunno..something else?? Maybe ops is a linked list, but that seems dumb 🙃.

Note: eventually this whole func can be closer to the badger impl which is a "streaming" iterator system, instead of loading all store values into an array.

Just noting that Option 2 can be made really quite efficient if we want to avoid anything too fancy here.

I changed the txn store to a btree so the ops are ordered. Check out the latest changes and let me know what you think.

I changed the txn store to a btree so the ops are ordered. Check out the latest changes and let me know what you think.

I did originally have this as an option, but removed it. Its basically trading efficiency between the individual ops (Put, Delete) and Commit. So individual ops are more expensive so the Commit is cheaper. Its certainly a valid option, just wanted to outline the (potential) downsides.

jsimnz · 2022-11-17T10:36:59Z

datastore/memory/txn.go

+	t.target.mu.Lock()
+	defer t.target.mu.Unlock()


This part makes things a bit tricky w.r.t the mutexs on the main store. In general, this transaction implementation doesn't protect against conflicts, its more akin to a basic batch, exposed as a transaction interface.

We could create a new lock for the target store, called txnmu or something (transaction mutex) which is a Read/Write mutex. The main store operations (Get, Set, Delete, etc...) can apply a read lock. And the transaction Commit() can apply a write lock.

This still won't give us "ACID" transactions, which we are pretty far from, but does give us better protection/semantics, as it means that all the operations from the transactions are applied, without getting overwritten during a commit.

Technically at the moment we have this "all operations" committed system with the current design, but thats because we are being very aggressive with the locks, which aren't necessary as Ive mentioned on the main store.

Check out the latest changes and let me know what you think.

datastore/txn.go

datastore/memory/memory.go

AndrewSisley · 2022-11-17T15:21:12Z

I gave it a quick scan and it looks good - will probably review in more detail in a bit, but nothing jumped out as needing serious attention. I do have a couple of general questions though - why do we need this, and what are we planning on using it for? In my eyes any serious use case would be much better off using badger-im or similar, and from memory it was surprisingly performant/lightweight too have you compared the benchmarks against this implementation?

fredcarle · 2022-11-17T16:55:32Z

I gave it a quick scan and it looks good - will probably review in more detail in a bit, but nothing jumped out as needing serious attention. I do have a couple of general questions though - why do we need this, and what are we planning on using it for? In my eyes any serious use case would be much better off using badger-im or similar, and from memory it was surprisingly performant/lightweight too have you compared the benchmarks against this implementation?

The main reason I created this is that after a discussion with John, we came to the conclusion that we don't want to use badger-im for the version store because of the overhead involved. Also, the currently used ds.MapDatastore is pretty bad so I decided to put something together that would fit our needs.

AndrewSisley · 2022-11-17T18:13:19Z

The main reason I created this is that after a discussion with John, we came to the conclusion that we don't want to use badger-im for the version store because of the overhead involved. Also, the currently used ds.MapDatastore is pretty bad so I decided to put something together that would fit our needs.

Are you guys sure the badger-im overhead is significant, and worth the risk to avoid?

And are we really sure we want to preserve the current versionedFetcher mechanic of creating a new temp-store, instead of directly fetching from the underlying persisted-stores?

jsimnz · 2022-11-18T07:06:49Z

Are you guys sure the badger-im overhead is significant, and worth the risk to avoid?

And are we really sure we want to preserve the current versionedFetcher mechanic of creating a new temp-store, instead of directly fetching from the underlying persisted-stores?

Yeah, Badger (even in memory) does a lot on initialization.

Heres the overhead of the two implementations, using badger.NewDatastore(...) and memory.NewDatastore(). Ensuring both aren't being optimized away etc...

jsimnz · 2022-11-18T07:14:17Z

Heres the benchmark code in case anyone is curious:
(Note the assignment operators are to ensure the compiler doesn't remove the New calls)
(Note2: I left the opts variable inside the loop as it seems safe to not re-use the opts between calls. I did try it without and it only reduces the allocs by 90 or so, which out of almost 4000 is kinda irrelevant :) )

var resultBadger *badgerds.Datastore
var resultBtree *memoryds.Datastore

func BenchmarkBadgerNew(b *testing.B) {
	var d *badgerds.Datastore
	for i := 0; i < b.N; i++ {
		opts := badgerds.Options{Options: badger.DefaultOptions("").WithInMemory(true)}
		d, _ = badgerds.NewDatastore("", &opts)
	}
	resultBadger = d
}

func BenchmarkBtreeNew(b *testing.B) {
	var d *memoryds.Datastore
	for i := 0; i < b.N; i++ {
		d = memoryds.NewDatastore()
	}
	resultBtree = d
}

AndrewSisley · 2022-11-18T13:18:47Z

Sweet - cheers for running that John - they look like sensible benchmarks. Badger-im is much heavier than I had in my head (maybe the vague memory in my head was just read-write benches?). I'd still be tempted to stick with badger anyway for time-travelling, as that is still only 0.4ms per query, but I do see why you guys are avoiding it :)

fredcarle · 2022-11-18T15:16:57Z

And are we really sure we want to preserve the current versionedFetcher mechanic of creating a new temp-store, instead of directly fetching from the underlying persisted-stores?

I don't understand the version fetcher enough at the moment to comment on this. @jsimnz can you add your input?

jsimnz · 2022-11-19T10:35:49Z

datastore/memory/txn.go

@@ -16,23 +16,24 @@ import (

 	ds "github.com/ipfs/go-datastore"
 	dsq "github.com/ipfs/go-datastore/query"
+	"github.com/tidwall/btree"
 )

 // basicTxn implements ds.Txn
 type basicTxn struct {
 	mu       sync.Mutex


suggestion: The Txn Mutex is now no longer necessary since youre using a btree instead of a map to store txn ops.

jsimnz · 2022-11-19T10:46:51Z

datastore/memory/txn.go

+	iterOpsHasMore := iterOps.Next()
 	for iter.Next() {
-		e := dsq.Entry{}
-		if op, exists := t.ops[ds.NewKey(iter.Key())]; exists {
-			handledOps[ds.NewKey(iter.Key())] = struct{}{}
-			if op.delete {
-				continue
-			}
-			e.Key = iter.Key()
-			e.Size = len(op.value)
-			if !q.KeysOnly {
-				e.Value = op.value
+		for {


suggestion: This either needs clear documentation on the intent/design of this entire looping mechanic, or it needs to be re-worked.

Im (slightly) feeling like it should be reworked as its a little all over the place. 2 nested for loops, then 2 nested if loops, with breaks and continues to track, followed by an additional for loop with its own break and continue. Feels like it could be more succinct.

Happy to make suggestions if you want :)

I reworked the looping mechanic. The nested loops are unavoidable if we care about the order of the keys. But you'll see that it's much simplified.

jsimnz · 2022-11-19T11:00:56Z

datastore/memory/memory.go

-	mu     sync.Mutex
+// Datastore uses a btree for internal storage.
+type Datastore struct {
+	txnmu  sync.Mutex


suggestion: I think we talked about this during the standup by might not have effectively communicated - this could be a sync.RWMutex and each regular Datastore operation can acquire a readlock, and the transaction commit can acquire a writelock.

That way regular (non-txn) ops dont step on eachother (read lock) and you can make sure the transaction is atomic (no other ops can happen when a txn is being commited)

I changed it. Let me know if that's what you meant.

AndrewSisley · 2022-11-21T14:34:02Z

datastore/memory/memory.go

+
+// Datastore uses a btree for internal storage.
+type Datastore struct {
+	txnmu  sync.RWMutex


thought: This datastore will run very poorly at scale - it is essentially single threaded and would represent a very serious bottleneck in any real-world system. The transaction also does not not thread-safe (particularly the iterators in Query), and the testing is really insufficient for any serious-usage.

Given that this type is public-public, it would be worth documenting this as it seems irresponsible for us to suggest to users that they should keep their data in it in it's present form. Looks like it'll work well for for the version stuff so long as planner remains single-threaded.

This datastore will run very poorly at scale - it is essentially single threaded and would represent a very serious bottleneck in any real-world system. The transaction also does not not thread-safe (particularly the iterators in Query)

What makes you say that? I disagree completely with that statement. I might be missing something in my analysis but if you're making that statement, please give an example to prove it.

Which bit?

The datastore itself is locked behind a single mutex - only single operation can be handled at once - regardless of where or what it might be, so your 256 core server is still only able to handle a single op at a time.

In txn.Query you are iterating over multiple iterators in-tandem without any locks, that doesn't look like it is safe?

Well, looks like @jsimnz and I got duped. tidwall/btree#22
The package does implement locks but not for the Map version. I had them initially and will put them back.

The datastore itself is locked behind a single mutex - only single operation can be handled at once - regardless of where or what it might be, so your 256 core server is still only able to handle a single op at a time.

(answering this as if lock was implemented). There can be "unlimited" reads at once but only one write. I don't think having multiple write at once is safe for a database.

In txn.Query you are iterating over multiple iterators in-tandem without any locks, that doesn't look like it is safe?

This was implemented with the thought that btee.Map implemented locks. Will fix.

(answering this as if lock was implemented). There can be "unlimited" reads at once but only one write. I don't think having multiple write at once is safe for a database.

Nothing can read if a write lock is held - a single write will lock any thread out of the whole datastore

Would you expect anything different?

There are many ways in which you can reduce the scope of any given lock, although at the moment due to the issue flagged in Put/Delete you aren't ever actually locking this mutex.

For example consider a store with two keys A and B. There is no reason to lock reads of the B value if the A value is being written to.

In larger real-world situations you can chunk this, so that you dont have a mutex per value etc

It is actually fairly easy to see this chunking mechanic in SQL implementations - there are a small number of operations (like creating indexes in Oracle...) that will lock an entire table, but I dont recall coming across one that would lock the entire database.

UPDATE: It might be quite unpleasant to do this properly if locking outside of the btree as the code is trying to do so now, you might need to change that, or accept and document that this is essentially a single-thread-only bottleneck.

AndrewSisley · 2022-11-21T14:37:24Z

datastore/memory/memory.go

+)
+
+// Datastore uses a btree for internal storage.
+type Datastore struct {


thought: If we are going to maintain our own datastore we should probably look at implementing the IterableDatastore interface too so that we dont have to shim it

Yes that will be implemented in a separate PR :)

AndrewSisley · 2022-11-21T14:50:11Z

datastore/memory/memory.go

+
+// Put implements ds.Put
+func (d *Datastore) Put(ctx context.Context, key ds.Key, value []byte) (err error) {
+	d.txnmu.RLock()


todo: It does look like this should be Lock and not RLock, as you are writing? Same for in Delete

No this is correct but there needs to be an other lock (see response above regarding no locks on btree.Map)

I think the mutex can be dropped then - if you are only calling ReadLock, it is not doing anything at all besides creating an illusion of thread-safety.

EDIT: To clarify - I am extremely skeptical that this doesnt need to be a WriteLock, but will see once you have made your other changes as it sounds like you have a cunning plan :)

@AndrewSisley It is very much doing something :)

The hint is that its called txnmu and not just mu. Basically, non-transactional operations ds.Put(), ds.Delete, etc... will acquire a read lock as they are single operations on the Btree (The Btree is already thread safe btw).

The goal is here is regarding the actual Txn type. During Commit, the basicTxn will aquire a write lock on that datastore txnmu so that it can commit all the ops contained within the transaction, without other operations conflicting with it. This is required for atomicity.

[Screams] You guys are exposing the lock and locking on it outside of the host object? I missed that - can you please please hide that behind a function on DataStore, with a very large and clear warning in the function documentation:

func (d *Datastore) Lock() { d.txnmu.Lock() }

Directly locking on an object you don't own is about the easiest way I know of in programming to generate really painful to debug and frequently occuring lock related issues 😅 😅 😅

Sorry for being a bit dramatic, but that is really smelly 😆 On the plus side, the code makes sense now 😁

The datastore owns the object. It was to be specific that this lock would only be used during a transaction.

AndrewSisley · 2022-11-21T15:04:24Z

datastore/memory/txn.go

+	// best effort allocation
+	re := make([]dsq.Entry, 0, t.ds.values.Len()+t.ops.Len())
+	iter := t.ds.values.Iter()
+	iterOps := t.ops.Iter()


to expand on my earlier comment RE thread-safety in transactions, even if foo.Iter() returned a perfectly cloned instance of the datastore that was 100% threadsafe, you'd still have a race condition here between calling t.ds.values.Iter() and t.ops.Iter().

I am somewhat doubtful that the iterables are that safe too, and I would be supprised if the values that they yield are set in iterator instantiation - meaning that when you iterate through them below their values may be changing causing Next and Value calls to return a jumbled mess.

Indeed they aren't safe. tidwall/btree#22. Will fix

~~This one is certainly a difficult one, but it is independent of the other comment you made (However they are related on the general concept of thread safety :) ).~~

The part that makes this difficult is the "Snapshot Isolation" mechanics missing from this implementation in general. Due to its complexity, I recommend we leave the SI mechanics for a follow up PR.

As far as ACID (Atomic, Consistent, Isolation, Durable) goes, this implementation is fairly atomic, semi consistent, not isolated, and durable. But its a process, and the only place this is used atm is the VersionedFetcher. Work will continue before its an officially supported general-purpose in-memory store.

AndrewSisley

the Write lock issue is very much a blocker for me, so just marking this as 'request changes'.

AndrewSisley

Happy with the design etc - was a good call, thanks Fred

mu is widely used in the go community to represent a sync.Mutex

fix typo

jsimnz

Few minor things, but its up to you on how you'd want to (or need to) handle them.

Marking this as approved for now, as its in a good enough state 👍.

jsimnz · 2022-12-15T22:16:37Z

datastore/memory/txn.go

+	if t.readOnly {
+		return ErrReadOnlyTxn
+	}
+	t.ops.Set(dsItem{key: key.String(), version: t.getTxnVersion(), val: value})


question: Can you run through the relationship between txn.dsVersion and txn.txnVersion? Especially since in the commitHandler we run ds.nextVerision before we actually set the value in the ds btree.

Seems like we don't need both of them. Lmk.

txn.dsVersion is the version of the datastore when the transaction was initiated. txn.txnVersion Is used simply to have a version that is higher than that of the txn.dsVersion while we operate the transaction. I could remove it and simply add 1 to txn.dsVersion and we would get the same result.

I removed txnVersion from both the Datastore and the transaction.

✅

jsimnz · 2022-12-15T22:19:09Z

datastore/memory/txn.go

+}
+
+// Query implements ds.Query
+func (t *basicTxn) Query(ctx context.Context, q dsq.Query) (dsq.Results, error) {


question: Technically Query needs to track the read keys like we do in Get via the isGet bool, since iterating is "reading" each key, so they need to be tracked for conflict checks. But whether we need this atm is debatable.

I think I'm already doing what you're suggesting.

jsimnz · 2022-12-15T22:25:07Z

datastore/memory/txn.go

+			txnVersion: t.getTxnVersion(),
+		},
+	)
+	t.ds.clearOldInFlightTxn(ctx)


suggestion: This seems like a heavy function to call on every txn.Discard.

If there are no other in flight transactions, it's a no-op. Otherwise, their might just be a handfull of other in-flight transaction and the btree iter will be quite fast. I wouldn't qualify that as a heavy function. The alternative was to run in on time.After(x) in the purgeOldVersions loop.

jsimnz · 2022-12-15T22:32:08Z

datastore/memory/txn.go

+	for iter.Next() {
+		expectedItem := t.ds.get(ctx, ds.NewKey(iter.Item().key), t.getDSVersion())
+		latestItem := t.ds.get(ctx, ds.NewKey(iter.Item().key), t.ds.getVersion())
+		if latestItem.isDeleted || latestItem.version != expectedItem.version {


question: I'm not 100% convinced on this conflict routine. Specifically the isDelete check.

If the last operation to an item before the start of a transaction is a Delete() then the latest version will be isDelete = true. If the current transaction Updates that value, that is a non-conflicting change, but this will mark is a conflict because of the isDelete check.

If im understanding this correctly.

I removed the check of isDeleted.

✅

…k#947) Relevant issue(s) sourcenetwork#946 Description This PR provides a thread safe in memory store that supports both ds.Batching and ds.TxnFeature. It uses a btree as storage.

fredcarle added feature New feature or request area/datastore Related to the datastore / storage engine system action/no-benchmark Skips the action that runs the benchmark. labels Nov 16, 2022

fredcarle added this to the DefraDB v0.4 milestone Nov 16, 2022

fredcarle requested a review from a team November 16, 2022 23:44

fredcarle self-assigned this Nov 16, 2022

fredcarle force-pushed the fredcarle/feat/in-memory-store branch from 13fffcc to 802b146 Compare November 17, 2022 01:08

jsimnz requested changes Nov 17, 2022

View reviewed changes

fredcarle force-pushed the fredcarle/feat/in-memory-store branch from 6c3c06a to 31f4147 Compare November 17, 2022 18:30

jsimnz reviewed Nov 19, 2022

View reviewed changes

AndrewSisley reviewed Nov 21, 2022

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AndrewSisley requested changes Nov 21, 2022

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AndrewSisley approved these changes Nov 21, 2022

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fredcarle force-pushed the fredcarle/feat/in-memory-store branch from 2c3e71c to dc5e25d Compare November 23, 2022 20:01

fredcarle requested review from jsimnz and AndrewSisley November 23, 2022 20:02

fredcarle force-pushed the fredcarle/feat/in-memory-store branch from dc5e25d to cea676e Compare November 23, 2022 20:03

fredcarle added 21 commits December 15, 2022 16:47

change from map to btree

be8db18

rename syncLock to mu

119fa41

mu is widely used in the go community to represent a sync.Mutex

apply feedback

998deab

change tnxmu to RWMutex

eb747d0

refactor query loop

fb9cc1d

add keyMytex

704db6a

remove the need for a close channel

c1d51c8

add serializable snapshot isolation

350c3a2

add compressor feature

d123897

fix typo

apply fixes and feedback

8b40993

clean up get functions

584f07f

fix compressor batching test

426729c

apply feedback and fix detect change error

cdc05f6

apply feedback

8c51926

add txn conflict checking

dc50406

change prameter of time after

e1139bd

add read-write conflict check

e5824fd

add inflight transaction tracking and commit channel

1b88d09

remove unnecessary code

96d8094

add early exit if no inFlightTxn

749339a

change: serialize puts

0a39dd9

jsimnz approved these changes Dec 15, 2022

View reviewed changes

make delete on non existing document a no-op

aceed6e

fredcarle force-pushed the fredcarle/feat/in-memory-store branch from d9b68fc to aceed6e Compare December 15, 2022 22:47

apply feedback

1f1b84b

fredcarle merged commit 532a9bb into develop Dec 16, 2022

fredcarle deleted the fredcarle/feat/in-memory-store branch December 16, 2022 05:19

fredcarle mentioned this pull request Dec 16, 2022

Btree based in-memory datastore #945

Closed

AndrewSisley mentioned this pull request Mar 31, 2023

fix: Fix deadlock on memory-datastore Close #1261

Closed

feat: Add thread safe transactional in-memory datastore #947

feat: Add thread safe transactional in-memory datastore #947

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fredcarle commented Nov 16, 2022 • edited Loading

Relevant issue(s)

Description

Tasks

How has this been tested?

codecov bot commented Nov 16, 2022 • edited Loading

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fredcarle commented Nov 16, 2022 •

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codecov bot commented Nov 16, 2022 •

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jsimnz commented Nov 18, 2022 •

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AndrewSisley commented Nov 18, 2022 •

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jsimnz Nov 19, 2022 •

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AndrewSisley Nov 21, 2022 •

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AndrewSisley Nov 21, 2022 •

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AndrewSisley Nov 21, 2022 •

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jsimnz Nov 21, 2022 •

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jsimnz Nov 21, 2022 •

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