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1. HMS will still compare requested writeid and cached table writeid to decide if the request can serve from cache
2. Every add/remove/alter/rename partition request will increment the table writeid. HMS will mark cached table entry invalid upon processing the first write message from notification log, and mark it valid and tag with the right writeid upon processing the commit message from notification log

Write

There is no change on HMS write side. HMS will write data into db and also put an entry in notification log.

Commit

When the transaction is committed, HMS will put writeid of the modified tables during the query into notification log. HMS will retrieve the writeid from db. As an optimization, HMS client may also pass a flag to indicate this is a read-only transaction, HMS would not pull writeid from db if it is read-onlyEvery write request will advance the write id for the table for both DML/DDL. The writeid will be marked committed locally in HMS client. The next read request is guaranteed to read from db until the notification log catch up to the commit message of the transaction commit, since the writeid is newer than the cache (the writeid for the transaction is committed locally, but is not committed on HMS until notification log catch up).

Cache update

In the previous discussion, we know if the cache is stale, HMS will serve the request from ObjectStore. We need to catch up the cache with the latest change. This can be done by the existing notification log based cache update mechanism. A thread in HMS constantly poll from notification log, update the cache with the entries from notification log. The interesting entries in notification log are table/partition writes, and corresponding commit transaction message. When processing table/partition writes, HMS will put the table/partition entry in cache. However, the entry is not immediately usable until the commit message of the corresponding writes is processed, and tag the ValidWriteIdList for all the entries modified by the transactionmark writeid of corresponding table entry committed.

Here is a complete flow for a cache update when write happen (and illustrated in the diagram):

1. The ValidWriteIdList of cached table is initially [11:7,8]
2. HMS 1 get a alter_table request. HMS 1 puts alter_table message to notification log
3. The transaction in HMS 1 get committed. HMS 1 puts commit message to notification log along with the writeid [12:7,8]
4. The cache update thread in HMS 2 will read the alter_table event from notification log, update the cache with the new version from notification log. However, the entry is not available for read as there’s no writeid associate with it is not updated yet
5. A read for the entry on HMS 2 will fetch from db since the entry is not available for read
6. The cache update thread will further read commit event from notification log, tag the entry with the writeid mark writeid 12 as committed, the tag of cached table entry changed to [12:7,8]
7. The next read from HMS 2 will serve from cache

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The use cases discussed so far are driven by a query. However, during the HMS startup, there’s a cache prewarm. HMS will fetch everything from db to cache. There is no particular query drives the process, that means we don’t have ValidWriteIdList of the query. Prewarm needs to generate ValidWriteIdList by itself. To do that, for every table, HMS will query the current global transaction state ValidTxnList (HiveTxnManager.getValidTxns), and then convert it to table specific ValidWriteIdList (HiveTxnManager.getValidWriteIds). As an optimization, we don’t have to invoke HiveTxnManager.getValidTxns per table. We can invoke it every couple of minutes. If ValidTxnList is outdated, we will get an outdated ValidWriteIdList. Next time when Hive read this entry, Metastore will fetch from the db even though it is in fact fresh. There’s no correctness issue, only impact performance in some cases. The other possibility is the entry changes after we fetches ValidWriteIdList. This is not unlikely as fetching all partitions of the table may take some time. If that happens, the cached entry is actually newer than the ValidWriteIdList. The next time Hive reads it will trigger a db read though it is not necessary. Again, there’s no correctness issue, only impact performance in some cases.

Maintain WriteId

HMS will maintain ValidWriteIdList for every cache entry when transactions are committed. The initial ValidWriteIdList is brought in by bootstrap. After that, for every commit message, HMS needs to:

1. Find the table writeids associated with the txnid, this can be done by a db lookup on TXN_TO_WRITE_ID table, or by processing ALLOC_WRITE_ID_EVENT message in the notification log. I will explain later in detail
2. Mark the writeid as committed in the ValidWriteIdList associated with the cached tables

As an optimization, we can save a db lookup in #1 by cache the writeid of modified tables of the transaction. Every modified table will generate a corresponding ALLOC_WRITE_ID_EVENT associate txnid with table writeid generated. Upon we receive commit message of the transaction, we can get the table writeids for the transaction. Thus we don’t need to do a db lookup to find the same information. However, in the initial commit message after bootstrap, we might miss some ALLOC_WRITE_ID_EVENT for the transaction. To address this issue, we will use this optimization unless we saw the open transaction event as well. Otherwise, HMS will still go to the db to fetch the writeids.

Deal with Rename

When we rename a table, writeids are renamed immediately on HMS (TxnHandler.onRename). However, cache won’t update immediately until it catches up the notification log. It is possible the cached table with the same table name is actually another table which is already dropped. To solve the issue, Hive session will fetch tableid of involved tables from db (must bypass cache) at the beginning of the transaction. It can be combined with HMS request for writeid. In every read request, HMS client need to pass tableid as well. HMS will compare the tableid with cached table. If it does not match, HMS will fetch the table from db instead.

External Table

Write id is not valid for external tables. And Hive won’t fetch ValidWriteIdList if the query source is external tables. Without ValidWriteIdList, HMS won’t able to check the staleness of the cache. To solve this problem, we will use the original eventually consistent model for external tables. That is, if the table is external table, Hive will pass null ValidWriteIdList to metastore API/CachedStore. Metastore cache won’t store ValidWriteIdList alongside the entry. When reading, CachedStore always retrieve the current copy. The original notification update will update the metadata of external tables, so we can eventually get updates from external changes.

Consistency Guarantee

Since the source of truth for cache is notification log, and the notification log is total ordered, the cache provides monotonic reads. The cost of that is we delay the update of cache until the notification log is caught up by the background thread. This guarantee the cache always move forward not backward. During the interim before HMS catch up the notification log, read will be served from db. The performance will suffer during this short period of time, but consider write operation is less often, the cost is minor.

The other benefit of this approach is it provide right semantic even if a transaction consists of more than one HMS write request. In that case, there are multiple copies of the cache entry could associate with a single writeid. For example, if there are two alter table request in the transaction, one request route to HMS 1 and the other route to HMS 2. We might not be able to tell which copy is applicable for this writeid if not carefully designed. By using notification log and only make cache available upon commit message, we can make sure we apply all request of the transaction. Once the commit message is processed, we can make sure the copy we have in cache is correct after this transaction.

The other thing to note is this approach does not This approach also provide read your own writes guarantee. Reads within the transaction cannot request newest copy which contains its own write, since the transaction is not committed thus the cached copy may not be correct. It will be correct until HMS apply all writes of the transaction from notification log. So the reads might end up reading the old copy from cache (consider the next read route to the other HMS). I am not sure if there’s a use case read the entry just written in Hive. If it does, we need to cache the written copy in client, so the next time client reads, it will be retrieved from client cache to make sure it contains its own writeswill use a writeid list which marks the current transaction committed, that’s guaranteed to be newer than the cached entry, and thus HMS will go to db to fetch the fresh copy.

Limitation

The check based on ValidWriteIdList is limited to table/partition. We cannot use the same mechanism for other entities such as databases, functions, privileges, as Hive only generate writeid on table (partition belong to table, so we use table writeid to track partition changes). Currently we don’t cache other entities, HMW will fetch those directly from db. However, many of those entities need to be in cache. For example, get_database is invoked multiple times by every query. So we need to address this issue in the future.

API changes

When reading, we need to pass a writeid list so HMS can compare it with the cached version. For every commit, we need to tell HMS what is the writeid for the tables changed during the transaction, so HMS can correctly tag the entry with the writeid. We need to add ValidWriteIdList into metastore thrift API and RawStore interfaces , including for all table/partition related read calls and commit transaction calls.

Hive_metastore.thriftthrift and HiveMetaStoreClient.java

Adding a serialized version of ValidWriteIdList to every read HMS API.

Actually we don’t need to add the new field into every read request because:

1. Many APIs are using a request structure rather than taking individual parameters. So need to add ValidWriteIdList to the request structure instead
2. Some APIs already take ValidWriteIdList to invalidate outdated transactional statistics. We don’t need to change the API signature, but will reuse the ValidWriteIdList to validate cached entries in CachedStore

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HMS read API will remain backward compatible for external table. That is, new server can deal with old client. If the old client issue a create_table call, server side will receive the request of create_table with tableid=0 and validWriteIdList=null, and will cache or retrieve the entry regardless(with eventual consistency model). For managed table, tableid and validWriteIdList will be are required and HMS server will throw an exception if validWriteIdList=null.

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Hive.java

The implementation details will be encapsulated in Hive.java. Which include:

1. Generate new write id for every write operation involving managed tables. Since DbTxnManager cache write id for every transaction, so every query will generate at most one new write id for a single table, even if it consists of multiple Hive.java write API calls
2. Retrieve table write id from config for every read operation if exists Pass the tableid and writeid to the read request of HMS client. It can be retrieved from config (for managed table, it guarantees to be there in config), and pass the write id to HMS API

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Changes in Other Components

All other components invoking HMS API directly (bypass Hive.java) will be changed to invoke the newer HMS API. This includes HCatalog, Hive streaming, etc, and other projects using HMS client such as Impala.

For every read request involving table/partitions, HMS client (HiveMetaStoreClient) need to pass a tableid and validWriteIdList string in addition to the existing arguments. tableid and validWriteIdList can be retrieved with txnMgr.getValidWriteIdsAndTblIds(). validWriteIdList can be null if it is external table, as HMS will return whatever in the cache for external table using eventual consistency. But if validWriteIdList=null for managed table, HMS will throw exception. validWriteIdList is a serialized form of [ValidReaderWriteIdList|https://github. com/apache/hive/blob/master/storage-api/src/java/org/apache/hadoop/hive/common/ValidReaderWriteIdList.java#L119]. Usually ValidReaderWriteIdList Usually ValidTxnWriteIdList can be obtained from [HiveTxnManager|https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/lockmgr/HiveTxnManager.java] using the following code snippet:

HiveTxnManager txnMgr = TxnManagerFactory.getTxnManagerFactory().getTxnManager(conf);
ValidTxnList txnIds = txnMgr.getValidTxns(); // get global transaction

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 state
ValidTxnWriteIdList
txnWriteIdsTblIds = txnMgr.

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getValidWriteIdsTableIds(txnTables, txnString); // map global transaction state to table specific write id

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int tblId = txnWriteIdsTblIds.getTableId(fullTableName);
ValidWriteIdList writeids = txnWriteIds.getTableValidWriteIdList(fullTableName); // get table specific writeid

For every managed table write, advance the writeid for the table:

AcidUtils.advanceWriteId(conf, tbl);