Added changes so that bin/*.sh files can work with CYGWIN under windows,...#13
Added changes so that bin/*.sh files can work with CYGWIN under windows,...#13aloklal99 wants to merge 1 commit into
Conversation
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Could you open an Apache Kafka jira and attach the patch there? This will take care of Apache licensing issues. Thanks, Jun |
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Done. I created this JIRA On Tue, Jan 21, 2014 at 9:09 PM, Jun Rao notifications@github.com wrote:
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@aloklal99, can you please close this PR then? (we can't do it ourselves without asking Apache Infra via a ticket) |
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Done. |
simplify onPartitionsRevoked action
Task state management
[LOGBROKER-897] copy jars before start
Windows fixes 1.0.0
…d clean up partitionState in PartitionStateMachine after topic deletion is done (apache#13) Exclude topics being deleted from the offlinePartitionCount metric and clean up partitionState in PartitionStateMachine after topic deletion is done Currently the offlinePartitionCount metric also reports the partitions of the topic that has already been queued for deletion, which creates noise for the alerting system, especially for the cluster that has frequent topic deletion operation. This patch adds a mechanism to exclude partitions already been queued for deletion from the offlinePartitionCount metric and also remove the in-memory topicsWithDeletionStarted in TopicDeletionManager since we no longer use it to update the metric. This patch also addresses a potential memory pressure issue of not cleaning up the in-memory partition states in PartitionStateMachine even after the topic has already been deleted.
…nt metric and clean up partitionState in PartitionStateMachine after topic deletion is done (apache#13) TICKET = LI_DESCRIPTION = Exclude topics being deleted from the offlinePartitionCount metric and clean up partitionState in PartitionStateMachine after topic deletion is done Currently the offlinePartitionCount metric also reports the partitions of the topic that has already been queued for deletion, which creates noise for the alerting system, especially for the cluster that has frequent topic deletion operation. This patch adds a mechanism to exclude partitions already been queued for deletion from the offlinePartitionCount metric and also remove the in-memory topicsWithDeletionStarted in TopicDeletionManager since we no longer use it to update the metric. This patch also addresses a potential memory pressure issue of not cleaning up the in-memory partition states in PartitionStateMachine even after the topic has already been deleted. EXIT_CRITERIA = MANUAL ["describe exit criteria"]
…nt metric and clean up partitionState in PartitionStateMachine after topic deletion is done (apache#13) TICKET = LI_DESCRIPTION = Exclude topics being deleted from the offlinePartitionCount metric and clean up partitionState in PartitionStateMachine after topic deletion is done Currently the offlinePartitionCount metric also reports the partitions of the topic that has already been queued for deletion, which creates noise for the alerting system, especially for the cluster that has frequent topic deletion operation. This patch adds a mechanism to exclude partitions already been queued for deletion from the offlinePartitionCount metric and also remove the in-memory topicsWithDeletionStarted in TopicDeletionManager since we no longer use it to update the metric. This patch also addresses a potential memory pressure issue of not cleaning up the in-memory partition states in PartitionStateMachine even after the topic has already been deleted. EXIT_CRITERIA = MANUAL ["describe exit criteria"]
…nt metric and clean up partitionState in PartitionStateMachine after topic deletion is done (apache#13) TICKET = LI_DESCRIPTION = Exclude topics being deleted from the offlinePartitionCount metric and clean up partitionState in PartitionStateMachine after topic deletion is done Currently the offlinePartitionCount metric also reports the partitions of the topic that has already been queued for deletion, which creates noise for the alerting system, especially for the cluster that has frequent topic deletion operation. This patch adds a mechanism to exclude partitions already been queued for deletion from the offlinePartitionCount metric and also remove the in-memory topicsWithDeletionStarted in TopicDeletionManager since we no longer use it to update the metric. This patch also addresses a potential memory pressure issue of not cleaning up the in-memory partition states in PartitionStateMachine even after the topic has already been deleted. EXIT_CRITERIA = MANUAL ["limiting this to LinkedIn branch only because we don't want to create offline partition noise for topics being deleting"]
…nt metric and clean up partitionState in PartitionStateMachine after topic deletion is done (apache#13) TICKET = LI_DESCRIPTION = Exclude topics being deleted from the offlinePartitionCount metric and clean up partitionState in PartitionStateMachine after topic deletion is done Currently the offlinePartitionCount metric also reports the partitions of the topic that has already been queued for deletion, which creates noise for the alerting system, especially for the cluster that has frequent topic deletion operation. This patch adds a mechanism to exclude partitions already been queued for deletion from the offlinePartitionCount metric and also remove the in-memory topicsWithDeletionStarted in TopicDeletionManager since we no longer use it to update the metric. This patch also addresses a potential memory pressure issue of not cleaning up the in-memory partition states in PartitionStateMachine even after the topic has already been deleted. EXIT_CRITERIA = MANUAL ["limiting this to LinkedIn branch only because we don't want to create offline partition noise for topics being deleting"]
…nt metric and clean up partitionState in PartitionStateMachine after topic deletion is done (apache#13) TICKET = LI_DESCRIPTION = Exclude topics being deleted from the offlinePartitionCount metric and clean up partitionState in PartitionStateMachine after topic deletion is done Currently the offlinePartitionCount metric also reports the partitions of the topic that has already been queued for deletion, which creates noise for the alerting system, especially for the cluster that has frequent topic deletion operation. This patch adds a mechanism to exclude partitions already been queued for deletion from the offlinePartitionCount metric and also remove the in-memory topicsWithDeletionStarted in TopicDeletionManager since we no longer use it to update the metric. This patch also addresses a potential memory pressure issue of not cleaning up the in-memory partition states in PartitionStateMachine even after the topic has already been deleted. EXIT_CRITERIA = MANUAL ["limiting this to LinkedIn branch only because we don't want to create offline partition noise for topics being deleting"]
…nt metric and clean up partitionState in PartitionStateMachine after topic deletion is done (apache#13) TICKET = LI_DESCRIPTION = Exclude topics being deleted from the offlinePartitionCount metric and clean up partitionState in PartitionStateMachine after topic deletion is done Currently the offlinePartitionCount metric also reports the partitions of the topic that has already been queued for deletion, which creates noise for the alerting system, especially for the cluster that has frequent topic deletion operation. This patch adds a mechanism to exclude partitions already been queued for deletion from the offlinePartitionCount metric and also remove the in-memory topicsWithDeletionStarted in TopicDeletionManager since we no longer use it to update the metric. This patch also addresses a potential memory pressure issue of not cleaning up the in-memory partition states in PartitionStateMachine even after the topic has already been deleted. EXIT_CRITERIA = MANUAL ["limiting this to LinkedIn branch only because we don't want to create offline partition noise for topics being deleting"]
…nt metric and clean up partitionState in PartitionStateMachine after topic deletion is done (apache#13) TICKET = LI_DESCRIPTION = Exclude topics being deleted from the offlinePartitionCount metric and clean up partitionState in PartitionStateMachine after topic deletion is done Currently the offlinePartitionCount metric also reports the partitions of the topic that has already been queued for deletion, which creates noise for the alerting system, especially for the cluster that has frequent topic deletion operation. This patch adds a mechanism to exclude partitions already been queued for deletion from the offlinePartitionCount metric and also remove the in-memory topicsWithDeletionStarted in TopicDeletionManager since we no longer use it to update the metric. This patch also addresses a potential memory pressure issue of not cleaning up the in-memory partition states in PartitionStateMachine even after the topic has already been deleted. EXIT_CRITERIA = MANUAL ["limiting this to LinkedIn branch only because we don't want to create offline partition noise for topics being deleting"]
…nt metric and clean up partitionState in PartitionStateMachine after topic deletion is done (apache#13) TICKET = LI_DESCRIPTION = Exclude topics being deleted from the offlinePartitionCount metric and clean up partitionState in PartitionStateMachine after topic deletion is done Currently the offlinePartitionCount metric also reports the partitions of the topic that has already been queued for deletion, which creates noise for the alerting system, especially for the cluster that has frequent topic deletion operation. This patch adds a mechanism to exclude partitions already been queued for deletion from the offlinePartitionCount metric and also remove the in-memory topicsWithDeletionStarted in TopicDeletionManager since we no longer use it to update the metric. This patch also addresses a potential memory pressure issue of not cleaning up the in-memory partition states in PartitionStateMachine even after the topic has already been deleted. EXIT_CRITERIA = MANUAL ["limiting this to LinkedIn branch only because we don't want to create offline partition noise for topics being deleting"]
MINOR: test fixes
Create an internal __cluster_link topic to store the source cluster metadata
a. By default it should be “compact” and retention.ms/bytes=-1” topic because we only need to store the latest record, and the key of one cluster-link should always be the same (i.e. the record key will be the cluster-link name (or UUID?))
New Config
- cluster.link.topic.num.partitions
- cluster.link.topic.replication.factor
```
./bin/kafka-configs.sh --bootstrap-server localhost:9092 --entity-type topics --entity-name __cluster_link --describe --all | grep retention
delete.retention.ms=86400000 sensitive=false synonyms={DEFAULT_CONFIG:log.cleaner.delete.retention.ms=86400000}
local.retention.bytes=-2 sensitive=false synonyms={DEFAULT_CONFIG:log.local.retention.bytes=-2}
local.retention.ms=-2 sensitive=false synonyms={DEFAULT_CONFIG:log.local.retention.ms=-2}
retention.bytes=-1 sensitive=false synonyms={DEFAULT_CONFIG:log.retention.bytes=-1}
retention.ms=-1 sensitive=false synonyms={DYNAMIC_TOPIC_CONFIG:retention.ms=-1}
```
New tests: - apache#8 Port conflict (HTTP == PLAINTEXT port) → rejected - apache#9 HTTP port=0 (random) works - apache#10 HTTP + HTTPS coexist on same broker - apache#11 advertised.listeners with HTTP parsed correctly - apache#12 HTTP without httpAcceptorFactory → IllegalStateException - apache#13 inter.broker.listener=HTTPS also rejected (not just HTTP) - apache#14 Custom listener name mapped to HTTP protocol (MY_REST_API:HTTP) - apache#15 HTTPS with valid SSL config succeeds All 15 SocketServerHttpTest pass. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Resolve all 9 Minor and 10 Info findings from the Checkpoint 1 code review, correcting factual inaccuracies, citation line-range imprecisions, and cross- artifact consistency drift. No modifications to pre-existing Kafka source, tests, build files, or comments — Audit Only rule preserved. Findings by file: accepted-mitigations.md #1 [MINOR] AclCache imports corrected: org.apache.kafka.server.immutable (PCollections-backed Kafka-internal) instead of Guava's com.google.common.collect. apache#2 [MINOR] API surface rewritten to reflect PCollections-style structural- sharing methods .updated()/.added()/.removed() instead of Guava builder pattern. apache#3 [MINOR] ZstdCompression BufferPool path split: wrap-for-output uses zstd-jni RecyclingBufferPool.INSTANCE (L55-L63), wrap-for- input uses ChunkedBytesStream (L65-L75), wrap-for-zstd-input uses anonymous Kafka-owned BufferPool delegating to BufferSupplier (L77-L98). apache#4 [INFO] MAX_RECORDS_PER_USER_OP citation corrected: declaration at QuorumController.java:L185; AclControlManager.java:L52 is the static import only. apache#5 [INFO] AclCache.removeAcl(Uuid) line corrected to L91-L103 (was L89+). references.md apache#6 [MINOR] SafeObjectInputStream citation range tightened from L17-L25 (class header + imports only) to L25-L62 covering the class declaration, DEFAULT_NO_DESERIALIZE_CLASS_NAMES blocklist (L27-L37), resolveClass (L43-L52), and isBlocked helper (L54-L62). apache#7 [INFO] PropertyFileLoginModule citation corrected to L42-L50, pointing at the Javadoc PLAINTEXT warning (L47-L48) plus the class declaration (L50). remediation-roadmap.md apache#8 [INFO] Gantt markers sanitised: all :done/:active markers replaced with :crit (illustrative critical emphasis) or plain markers to avoid any visual suggestion of work already performed. Explanatory blockquote added clarifying the marker change. severity-matrix.md apache#9 [MINOR] 7 occurrences of parenthesised '(Accepted Mitigation)' replaced with bracketed '[Accepted Mitigation]' per Global Conventions for plain-text markers. Cross-validated 9 bracketed instances, 0 parenthesised remaining. README.md apache#11 [MINOR] HEAD commit reference corrected to the pre-audit baseline 6d16f68 (was 8a99096, a mid-audit snapshot); baseline attestation now refers to the commit immediately before the audit began. apache#12 [MINOR] Snapshot date unified to 2026-04-17 across all artifacts. apache#14 [INFO] '25 files' claim qualified as 'planned at project completion' vs 'delivered at this checkpoint (15 files)'. attack-surface-map.md apache#16 [MINOR] Clients module category count corrected from 'six' to 'nine' (actual Mermaid edges: C1, C2, C3, C4, C5, C7, C8, C9, C10). apache#17 [MINOR] Connect module category count corrected from 'five' to 'seven' (actual Mermaid edges: C1, C4, C6, C7, C8, C9, C10). oauth-jwt-validation-paths.md apache#18 [INFO] Outer citation ranges tightened: BrokerJwtValidator.configure at L107-L138 (not L102-L134); OAuthBearerUnsecuredValidatorCallbackHandler.handleCallback at L154-L177 (not L161-L204, which spanned unrelated helpers); allowableClockSkewMs helper cited separately at L194-L207. executive-summary.html Cross-ref A [MINOR] HEAD commit aligned to 6d16f68 at three sites (L621, L668, L1544); methodology Mermaid node re-labelled 'Baseline 6d16f68'. Cross-ref B [MINOR] Snapshot date aligned to 2026-04-17 at two sites (L619, L1542). Out-of-scope (Info-level forward-refs): apache#10, apache#13, apache#15 — Links to docs/security-audit/findings/*.md deliverables not yet present at Checkpoint 1; expected per scope boundary; will resolve at Checkpoint 2 when the 10 per-category findings files land. Validation results (Phase 3): - Mermaid fences: all balanced (20 blocks total, all typed) - HTML tag balance: 22 sections + all 20+ tag types balanced - CDNs intact: reveal.js 5.1.0, Mermaid 11.4.0, Font Awesome 6.6.0 - Emojis: zero across all 15 artifacts - TODOs/placeholders introduced: zero - Gantt markers: :crit + plain only (no :done/:active) - Cross-artifact consistency: zero wrong SHA/date values remaining - Citation ranges: 12 verified against AclCache, QuorumController, AclControlManager, ZstdCompression, SafeObjectInputStream, PropertyFileLoginModule, BrokerJwtValidator, and OAuthBearerUnsecuredValidatorCallbackHandler. Audit Only rule verification: git diff --name-status 6d16f68..HEAD returns only 'A' entries, all under docs/security-audit/. Zero modifications, deletions, or renames of any pre-existing Kafka path.
Background
The script files to run Kafka under Windows don't work as is. One needs to hand tweak them since their location is not
binbutbin/windows. Further, the script files underbin/windowsare not a complete replica of those underbin. To be sure, this isn't a complaint. To the contrary most projects now-a-days don't bother to support running on Windows or do so very late. Just that because of these limitation it might be more prudent to make the script files underbinitself run under windows rather than trying to make the files underbin/windowswork or to make them complete.Change Summary
Most common unix-like shell on windows is the bash shell which is a part of the cygwin project. Out of the box the scripts don't work mostly due to peculiarities of the directory paths and class path separators. This change set makes a focused change to a single file under
binso that all of the script files underbinwould work as is on windows platform when using bash shell of Cygwin distribution.Motivation
Acceptance of this change would enable a vast body of developers that use (or have to use) Windows as their development/testing/production platform to use Kafka's with ease. More importantly by making the running of examples smoothly on Windoes+Cygwin-bash it would make the process of evaluation of Kafka simpler and smoother and potentially make for a favorable evaluation. For, it would show commitment of the Kafka team to espouse deployments on Windows (albeit only under cygwin). Further, as the number of people whom use Kafka on Windows increases, one would attract people who can eventually fix the script files under
bin/Windowsitself so that need to run under Cygwin would also go away, too.Testing details
The change have been tested under
GNU bash, version 4.1.11(2)-release (x86_64-unknown-cygwin)running on Windows 7 Enterprise.