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luzhijing pushed a commit to branch master
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The following commit(s) were added to refs/heads/master by this push:
new 7d9ed8aff839 Update Slack link (#527)
7d9ed8aff839 is described below
commit 7d9ed8aff839166ad10c83e7f7847abaed6b6c2d
Author: Hu Yanjun <100749531+httpshir...@users.noreply.github.com>
AuthorDate: Tue Apr 9 18:50:49 2024 +0800
Update Slack link (#527)
---
...nchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md | 2 +-
...cs-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md | 2 +-
blog/Building-a-Data-Warehouse-for-Traditional-Industry.md | 2 +-
...Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md | 6 +-----
blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md | 2 +-
...w-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md | 2 +-
...Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md | 2 +-
blog/Improving-Query-Speed-to-Make-the-Most-out-of-Your-Data.md | 2 +-
...the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md | 2 +-
blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md | 2 +-
...5-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md | 2 +-
...-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md | 2 +-
blog/Say-Goodbye-to-OOM-Crashes.md | 2 +-
...-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md | 8 ++------
blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md | 2 +-
blog/Understanding-Data-Compaction-in-3-Minutes.md | 2 +-
...gh-available-real-time-data-warehouse-based-on-apache-doris.md | 2 +-
...nti-fraud-solution-based-on-the-apache-doris-data-warehouse.md | 2 +-
...is-speeds-up-data-reporting-tagging-and-data-lake-analytics.md | 2 +-
...3-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md | 2 +-
blog/auto-increment-columns-in-databases.md | 3 ++-
blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md | 2 +-
...treaming-what-happens-in-real-time-is-analyzed-in-real-time.md | 2 +-
...-cyber-security-by-enabling-seven-times-faster-log-analysis.md | 2 +-
...csearch-to-apache-doris-upgrading-an-observability-platform.md | 4 ++--
...ves-in-real-time-iov-data-analytics-helps-prevent-accidents.md | 2 +-
...-to-apache-doris-a-next-generation-real-time-data-warehouse.md | 2 +-
...ted-index-accelerates-text-searches-by-40-time-apache-doris.md | 2 +-
blog/log-analysis-elasticsearch-vs-apache-doris.md | 2 +-
blog/migrating-from-clickhouse-to-apache-doris-what-happened.md | 2 +-
blog/release-note-2.0.0.md | 2 +-
blog/release-note-2.1.0.md | 2 +-
blog/variant-in-apache-doris-2.1.md | 2 +-
33 files changed, 36 insertions(+), 43 deletions(-)
diff --git
a/blog/Auto-Synchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md
b/blog/Auto-Synchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md
index d7988c36ac15..df9599715a46 100644
--- a/blog/Auto-Synchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md
+++ b/blog/Auto-Synchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md
@@ -190,5 +190,5 @@ CREATE TABLE doris_sink (
);
```
-If you've got any questions, find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog).
+If you've got any questions, find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
diff --git
a/blog/Building-A-Log-Analytics-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md
b/blog/Building-A-Log-Analytics-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md
index 7954ad923f96..0e4da60eff19 100644
---
a/blog/Building-A-Log-Analytics-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md
+++
b/blog/Building-A-Log-Analytics-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md
@@ -247,4 +247,4 @@ For more feature introduction and usage guide, see
documentation: [Inverted Inde
In a word, what contributes to Apache Doris' 10-time higher cost-effectiveness
than Elasticsearch is its OLAP-tailored optimizations for inverted indexing,
supported by the columnar storage engine, massively parallel processing
framework, vectorized query engine, and cost-based optimizer of Apache Doris.
-As proud as we are about our own inverted indexing solution, we understand
that self-published benchmarks can be controversial, so we are open to
[feedback](https://t.co/KcxAtAJZjZ) from any third-party users and see how
[Apache Doris](https://github.com/apache/doris) works in real-world cases.
+As proud as we are about our own inverted indexing solution, we understand
that self-published benchmarks can be controversial, so we are open to
[feedback](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
from any third-party users and see how [Apache
Doris](https://github.com/apache/doris) works in real-world cases.
diff --git a/blog/Building-a-Data-Warehouse-for-Traditional-Industry.md
b/blog/Building-a-Data-Warehouse-for-Traditional-Industry.md
index f33ebe0b1985..ce86bc950bb8 100644
--- a/blog/Building-a-Data-Warehouse-for-Traditional-Industry.md
+++ b/blog/Building-a-Data-Warehouse-for-Traditional-Industry.md
@@ -172,4 +172,4 @@ Actually, before we evolved into our current data
architecture, we tried Hive, S
On the other hand, to smoothen our big data transition, we need to make our
data platform as simple as possible in terms of usage and maintenance. That's
why we landed on Apache Doris. It is compatible with MySQL protocol and
provides a rich collection of functions so we don't have to develop our own
UDFs. Also, it is composed of only two types of processes: frontends and
backends, so it is easy to scale and track.
-Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog).
+Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
diff --git
a/blog/Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md
b/blog/Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md
index bb3877349ba0..29ec7a8a0bbd 100644
--- a/blog/Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md
+++ b/blog/Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md
@@ -241,10 +241,6 @@ Contact d...@apache.doris.org to join the Lakehouse
SIG(Special Interest Group) i
**# Links:**
-**SelectDB:**
-
-https://selectdb.com
-
**Apache Doris:**
http://doris.apache.org
@@ -253,5 +249,5 @@ http://doris.apache.org
https://github.com/apache/doris
-Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog).
+Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
diff --git a/blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md
b/blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md
index 54c7f8c5db7f..ccb1ed66dee5 100644
--- a/blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md
+++ b/blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md
@@ -134,7 +134,7 @@ The results are as below:
In short, what contributed to the fast data loading and data queries in this
case?
- The Colocate mechanism that's designed for distributed computing
-- Collaboration between database users and
[developers](https://t.co/ZxJuNJHXb2) that enables the operator merging
+- Collaboration between database users and
[developers](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
that enables the operator merging
- Support for a wide range of data loading methods to choose from
- A vectorized engine that brings overall performance increase
diff --git
a/blog/Database-in-Fintech-How-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md
b/blog/Database-in-Fintech-How-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md
index 1dc63a4d3f06..31c3ec3c4d5e 100644
---
a/blog/Database-in-Fintech-How-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md
+++
b/blog/Database-in-Fintech-How-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md
@@ -72,7 +72,7 @@ Analysts often check data reports of the same metrics on a
regular basis. These
The complexity of data analysis in the financial industry lies in the data
itself other than the engineering side. Thus, the underlying data architecture
should focus on facilitating the unified and efficient management of data.
Apache Doris provides the flexibility of simple metric registration and the
ability of fast and resource-efficient metric computation. In this case, the
user is able to handle 10,000 active financial metrics in 10,000 dashboards
with 30% less ETL efforts.
-Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog).
+Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
diff --git
a/blog/For-Entry-Level-Data-Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md
b/blog/For-Entry-Level-Data-Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md
index 7162d3d19aa7..1f842b20f31e 100644
---
a/blog/For-Entry-Level-Data-Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md
+++
b/blog/For-Entry-Level-Data-Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md
@@ -100,4 +100,4 @@ Firstly, Apache Doris is famously fast in Join queries. So
if you need to extrac
## Conclusion
-This is the overview of a simple data architecture and how it can provide the
data services you need. It ensures data ingestion stability and quality with
Flink CDC, and quick data analysis with Apache Doris. The deployment of this
architecture is simple, too. If you plan for a data analytic upgrade for your
business, you might refer to this case. If you need advice and help, you may
join our [community here](https://t.co/ZxJuNJHXb2).
+This is the overview of a simple data architecture and how it can provide the
data services you need. It ensures data ingestion stability and quality with
Flink CDC, and quick data analysis with Apache Doris. The deployment of this
architecture is simple, too. If you plan for a data analytic upgrade for your
business, you might refer to this case. If you need advice and help, you may
join our [community
here](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W22
[...]
diff --git a/blog/Improving-Query-Speed-to-Make-the-Most-out-of-Your-Data.md
b/blog/Improving-Query-Speed-to-Make-the-Most-out-of-Your-Data.md
index 1033c3c71bce..0c99cb575ee7 100644
--- a/blog/Improving-Query-Speed-to-Make-the-Most-out-of-Your-Data.md
+++ b/blog/Improving-Query-Speed-to-Make-the-Most-out-of-Your-Data.md
@@ -117,4 +117,4 @@ As we set out to find a single data warehouse that could
serve all our needs, we
**Try** [**Apache Doris**](https://github.com/apache/doris) **out!**
-It is an open source real-time analytical database based on MPP architecture.
It supports both high-concurrency point queries and high-throughput complex
analysis. Or you can start your free trial of
[**SelectDB**](https://en.selectdb.com/), a cloud-native real-time data
warehouse developed based on the Apache Doris open source project by the same
key developers.
+It is an open source real-time analytical database based on MPP architecture.
It supports both high-concurrency point queries and high-throughput complex
analysis.
diff --git
a/blog/Is-Your-Latest-Data-Really-the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md
b/blog/Is-Your-Latest-Data-Really-the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md
index e3841ab440c5..738f773b904d 100644
---
a/blog/Is-Your-Latest-Data-Really-the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md
+++
b/blog/Is-Your-Latest-Data-Really-the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md
@@ -223,5 +223,5 @@ mysql> select * from test_table;
## Conclusion
-Congratulations. Now you've gained an overview of how data updates are
implemented in Apache Doris. With this knowledge, you can basically guarantee
efficiency and accuracy of data updating. But wait, there is so much more about
that. As Apache Doris 2.0 is going to provide more powerful Partial Column
Update capabilities, with improved execution of the Update statement and the
support for more complicated multi-table Join queries, I will show you how to
take advantage of them in details [...]
+Congratulations. Now you've gained an overview of how data updates are
implemented in Apache Doris. With this knowledge, you can basically guarantee
efficiency and accuracy of data updating. But wait, there is so much more about
that. As Apache Doris 2.0 is going to provide more powerful Partial Column
Update capabilities, with improved execution of the Update statement and the
support for more complicated multi-table Join queries, I will show you how to
take advantage of them in details [...]
diff --git a/blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md
b/blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md
index 95c6e0245506..656a370e4d77 100644
--- a/blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md
+++ b/blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md
@@ -102,4 +102,4 @@ We believe self-service BI is the future in the BI
landscape, just like AGI is t
-Find the Apache Doris developers on [Slack](https://t.co/ZxJuNJHXb2)
+Find the Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
diff --git
a/blog/Log-Analysis-How-to-Digest-15-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md
b/blog/Log-Analysis-How-to-Digest-15-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md
index 13bc55383c1a..7c5258866735 100644
---
a/blog/Log-Analysis-How-to-Digest-15-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md
+++
b/blog/Log-Analysis-How-to-Digest-15-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md
@@ -87,7 +87,7 @@ These strategies have shortened the response time of queries.
For example, a que
## Ongoing Plans
-The user is now testing with the newly added [inverted
index](https://doris.apache.org/docs/dev/data-table/index/inverted-index?_highlight=inverted)
in Apache Doris. It is designed to speed up full-text search of strings as
well as equivalence and range queries of numerics and datetime. They have also
provided their valuable feedback about the auto-bucketing logic in Doris:
Currently, Doris decides the number of buckets for a partition based on the
data size of the previous partition. T [...]
+The user is now testing with the newly added [inverted
index](https://doris.apache.org/docs/dev/data-table/index/inverted-index?_highlight=inverted)
in Apache Doris. It is designed to speed up full-text search of strings as
well as equivalence and range queries of numerics and datetime. They have also
provided their valuable feedback about the auto-bucketing logic in Doris:
Currently, Doris decides the number of buckets for a partition based on the
data size of the previous partition. T [...]
diff --git
a/blog/Replacing-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md
b/blog/Replacing-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md
index e65f961f950a..4b2788f43d20 100644
---
a/blog/Replacing-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md
+++
b/blog/Replacing-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md
@@ -113,7 +113,7 @@ We have 2 clusters in Apache Doris accommodating tens of
TBs of data, with almos
-Lastly, I would like to share with you something that interested us most when
we first talked to the [Apache Doris community](https://t.co/KcxAtAJZjZ):
+Lastly, I would like to share with you something that interested us most when
we first talked to the [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ):
- Apache Doris supports data ingestion transactions so it can ensure data is
written **exactly once**.
- It is well-integrated with the data ecosystem and can smoothly interface
with most data sources and data formats.
diff --git a/blog/Say-Goodbye-to-OOM-Crashes.md
b/blog/Say-Goodbye-to-OOM-Crashes.md
index 81c39eb225f1..7f51902ee707 100644
--- a/blog/Say-Goodbye-to-OOM-Crashes.md
+++ b/blog/Say-Goodbye-to-OOM-Crashes.md
@@ -163,5 +163,5 @@ If the process memory consumed is beyond the MemLimit (90%
of total system memor
After optimizations in memory allocation, memory tracking, and memory limit,
we have substantially increased the stability and high-concurrency performance
of Apache Doris as a real-time analytic data warehouse platform. OOM crash in
the backend is a rare scene now. Even if there is an OOM, users can locate the
problem root based on the logs and then fix it. In addition, with more flexible
memory limits on queries and data ingestion, users don't have to spend extra
effort taking care of [...]
-In the next phase, we plan to ensure completion of queries in memory
overcommitment, which means less queries will have to be canceled due to memory
shortage. We have broken this objective into specific directions of work:
exception safety, memory isolation between resource groups, and the flushing
mechanism of intermediate data. If you want to meet our developers, [this is
where you find us](https://t.co/XD4uUSROft).
+In the next phase, we plan to ensure completion of queries in memory
overcommitment, which means less queries will have to be canceled due to memory
shortage. We have broken this objective into specific directions of work:
exception safety, memory isolation between resource groups, and the flushing
mechanism of intermediate data. If you want to meet our developers, [this is
where you find
us](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
diff --git
a/blog/Tencent-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md
b/blog/Tencent-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md
index 3860417da27f..d5fdff3e50ec 100644
--- a/blog/Tencent-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md
+++ b/blog/Tencent-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md
@@ -241,16 +241,12 @@ Doris’ capability of cold and hot data separation
provides the foundation of o
# Conclusion
-Thank you for scrolling all the way down here and finishing this long read.
We’ve shared our cheers and tears, lessons learned, and a few practices that
might be of some value to you during our transition from ClickHouse to Doris.
We really appreciate the help from the Apache Doris community and the
[SelectDB](https://selectdb.com) team, but we might still be chasing them
around for a while since we attempt to realize auto-identification of cold and
hot data, pre-computation of frequentl [...]
+Thank you for scrolling all the way down here and finishing this long read.
We’ve shared our cheers and tears, lessons learned, and a few practices that
might be of some value to you during our transition from ClickHouse to Doris.
We really appreciate the help from the Apache Doris community, but we might
still be chasing them around for a while since we attempt to realize
auto-identification of cold and hot data, pre-computation of frequently used
tags/metrics, simplification of code lo [...]
**# Links**
-**SelectDB**:
-
-https://selectdb.com
-
**Apache Doris**:
http://doris.apache.org
@@ -259,4 +255,4 @@ http://doris.apache.org
https://github.com/apache/doris
-Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog)
+Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
diff --git a/blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md
b/blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md
index 1df76bb243c3..ea0befab3be5 100644
--- a/blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md
+++ b/blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md
@@ -353,7 +353,7 @@ Apache Doris 2.0 has been optimized for cold data queries.
Only the first-time a
In Apache Doris, each data ingestion leads to the generation of a new Rowset,
so the update of historical data will be put in a Rowset that is separated from
those of newly loaded data. That’s how it makes sure the updating of cold data
does not interfere with the ingestion of hot data. Once the rowsets cool down,
they will be moved to S3 and deleted locally, and the updated historical data
will go to the partition where it belongs.
-If you any questions, come find Apache Doris developers on
[Slack](https://t.co/ZxJuNJHXb2). We will be happy to provide targeted support.
+If you any questions, come find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
We will be happy to provide targeted support.
diff --git a/blog/Understanding-Data-Compaction-in-3-Minutes.md
b/blog/Understanding-Data-Compaction-in-3-Minutes.md
index e7972fc696d6..7bfaccf7f67f 100644
--- a/blog/Understanding-Data-Compaction-in-3-Minutes.md
+++ b/blog/Understanding-Data-Compaction-in-3-Minutes.md
@@ -128,4 +128,4 @@ Every data engineer has somehow been harassed by
complicated parameters and conf
## Conclusion
-This is how we keep our "storekeepers" working efficiently and
cost-effectively. If you wonder how these strategies and optimization work in
real practice, we tested Apache Doris with ClickBench. It reaches a
**compaction speed of 300,000 row/s**; in high-concurrency scenarios, it
maintains **a stable compaction score of around 50**. Also, we are planning to
implement auto-tuning and increase observability for the compaction mechanism.
If you are interested in the [Apache Doris](https:// [...]
+This is how we keep our "storekeepers" working efficiently and
cost-effectively. If you wonder how these strategies and optimization work in
real practice, we tested Apache Doris with ClickBench. It reaches a
**compaction speed of 300,000 row/s**; in high-concurrency scenarios, it
maintains **a stable compaction score of around 50**. Also, we are planning to
implement auto-tuning and increase observability for the compaction mechanism.
If you are interested in the [Apache Doris](https:// [...]
diff --git
a/blog/a-fast-secure-high-available-real-time-data-warehouse-based-on-apache-doris.md
b/blog/a-fast-secure-high-available-real-time-data-warehouse-based-on-apache-doris.md
index 525eb7808cf9..9f35b0230dd8 100644
---
a/blog/a-fast-secure-high-available-real-time-data-warehouse-based-on-apache-doris.md
+++
b/blog/a-fast-secure-high-available-real-time-data-warehouse-based-on-apache-doris.md
@@ -146,4 +146,4 @@ Disaster recovery is crucial for the financial industry.
The user leverages the
## Conclusion
-We appreciate the user for their active
[communication](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog)
with us along the way and are glad to see so many Apache Doris features fit in
their needs. They are also planning on exploring federated query,
compute-storage separation, and auto maintenance with Apache Doris. We look
forward to more best practice and feedback from them.
\ No newline at end of file
+We appreciate the user for their active
[communication](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
with us along the way and are glad to see so many Apache Doris features fit in
their needs. They are also planning on exploring federated query,
compute-storage separation, and auto maintenance with Apache Doris. We look
forward to more best practice and feedback from them.
\ No newline at end of file
diff --git
a/blog/a-financial-anti-fraud-solution-based-on-the-apache-doris-data-warehouse.md
b/blog/a-financial-anti-fraud-solution-based-on-the-apache-doris-data-warehouse.md
index c92b763936d6..f6c81920043f 100644
---
a/blog/a-financial-anti-fraud-solution-based-on-the-apache-doris-data-warehouse.md
+++
b/blog/a-financial-anti-fraud-solution-based-on-the-apache-doris-data-warehouse.md
@@ -104,4 +104,4 @@ So far, the bank has added nearly 100 alerting rules for
various risk types to t
## Conclusion
-For a comprehensive anti-fraud solution, the bank conducts full-scale
real-time monitoring and reporting for all their data workflows. Then, for each
transaction, they look into the multiple dimensions of it to identify risks.
For the suspicious transactions reported by the bank customers, they perform
federated queries to retrieve the full details of them. Also, an auto alerting
mechanism is always on patrol to safeguard the whole system. These are the
various types of analytic workload [...]
\ No newline at end of file
+For a comprehensive anti-fraud solution, the bank conducts full-scale
real-time monitoring and reporting for all their data workflows. Then, for each
transaction, they look into the multiple dimensions of it to identify risks.
For the suspicious transactions reported by the bank customers, they perform
federated queries to retrieve the full details of them. Also, an auto alerting
mechanism is always on patrol to safeguard the whole system. These are the
various types of analytic workload [...]
\ No newline at end of file
diff --git
a/blog/apache-doris-speeds-up-data-reporting-tagging-and-data-lake-analytics.md
b/blog/apache-doris-speeds-up-data-reporting-tagging-and-data-lake-analytics.md
index cf66facea2dc..068f7cc4327c 100644
---
a/blog/apache-doris-speeds-up-data-reporting-tagging-and-data-lake-analytics.md
+++
b/blog/apache-doris-speeds-up-data-reporting-tagging-and-data-lake-analytics.md
@@ -88,6 +88,6 @@ For easier deployment, they have also optimized their Deploy
on Yarn process via
## Conclusion
-For data reporting and customer tagging, Apache Doris smoothens data ingestion
and merging steps, and delivers high query performance based on its own design
and functionality. For data lake analytics, the user improves resource
efficiency by elastic scaling of clusters using the Compute Node. Along their
journey with Apache Doris, they have also developed a data ingestion task
prioritizing mechanism and contributed it to the Doris project. A gesture to
facilitate their use case ends up [...]
+For data reporting and customer tagging, Apache Doris smoothens data ingestion
and merging steps, and delivers high query performance based on its own design
and functionality. For data lake analytics, the user improves resource
efficiency by elastic scaling of clusters using the Compute Node. Along their
journey with Apache Doris, they have also developed a data ingestion task
prioritizing mechanism and contributed it to the Doris project. A gesture to
facilitate their use case ends up [...]
Check Apache Doris [repo](https://github.com/apache/doris) on GitHub
\ No newline at end of file
diff --git
a/blog/apache-doris-summit-asia-2023-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md
b/blog/apache-doris-summit-asia-2023-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md
index 89ae8c16ec70..52b061329f3d 100644
---
a/blog/apache-doris-summit-asia-2023-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md
+++
b/blog/apache-doris-summit-asia-2023-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md
@@ -174,4 +174,4 @@ From the self-developed pre-aggregation storage engine,
materialized views, and
- We want to keep inspiring the data world by presenting more use cases.
- We want to provide more and better choices for users by collaborating with
partners along the data pipeline and cloud service providers.
-By choosing Apache Doris, you choose to stay in the heartbeat of innovation.
The [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog)
awaits newcomers.
+By choosing Apache Doris, you choose to stay in the heartbeat of innovation.
The [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
awaits newcomers.
diff --git a/blog/auto-increment-columns-in-databases.md
b/blog/auto-increment-columns-in-databases.md
index 0d8a43ca7b05..85d02032f746 100644
--- a/blog/auto-increment-columns-in-databases.md
+++ b/blog/auto-increment-columns-in-databases.md
@@ -409,4 +409,5 @@ Attention is required regarding:
## Conclusion
-AUTO_INCREMENT brings higher stability and reliability for Doris in
large-scale data processing. If it sounds like something you need, download
[Apache Doris](https://doris.apache.org/download/) and try it out. For issues
you come across along the way, join us in the [Apache Doris developer and user
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog)
and we are happy to help.
\ No newline at end of file
+AUTO_INCREMENT brings higher stability and reliability for Doris in
large-scale data processing. If it sounds like something you need, download
[Apache Doris](https://doris.apache.org/download/) and try it out. For issues
you come across along the way, join us in the [Apache Doris developer and user
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
and we are happy to help.
+
diff --git a/blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md
b/blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md
index 7c204ce1b4b7..6ba83ebeae5e 100644
--- a/blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md
+++ b/blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md
@@ -131,4 +131,4 @@ In Apache Doris, this is implemented by the BITMAP
functions: `BITMAP_CONTAINS`
## Conclusion
-From CDP 1.0 to CDP 2.0, the insurance company adopts Apache Doris, a unified
data warehouse, to replace Spark+Impala+HBase+NebulaGraph. That increases their
data processing efficiency by breaking down the data silos and streamlining
data processing pipelines. In CDP 3.0 to come, they want to group their
customer by combining real-time tags and offline tags for more diversified and
flexible analysis. The [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite [...]
\ No newline at end of file
+From CDP 1.0 to CDP 2.0, the insurance company adopts Apache Doris, a unified
data warehouse, to replace Spark+Impala+HBase+NebulaGraph. That increases their
data processing efficiency by breaking down the data silos and streamlining
data processing pipelines. In CDP 3.0 to come, they want to group their
customer by combining real-time tags and offline tags for more diversified and
flexible analysis. The [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite [...]
\ No newline at end of file
diff --git
a/blog/data-analysis-for-live-streaming-what-happens-in-real-time-is-analyzed-in-real-time.md
b/blog/data-analysis-for-live-streaming-what-happens-in-real-time-is-analyzed-in-real-time.md
index 378569f0b563..7af596ecde6a 100644
---
a/blog/data-analysis-for-live-streaming-what-happens-in-real-time-is-analyzed-in-real-time.md
+++
b/blog/data-analysis-for-live-streaming-what-happens-in-real-time-is-analyzed-in-real-time.md
@@ -213,7 +213,7 @@ limit 1,10;
## Conclusion
-Data analysis in live streaming is challenging for the underlying database,
but it is also where the key competitiveness of Apache Doris comes to play.
First of all, Apache Doris can handle most data processing workloads, so
platform builders don't have to worry about putting many components together
and consequential maintenance issues. Secondly, it has a lot of
query-accelerating features, including but not limited to indexes. After
tackling the speed issues, the [Apache Doris develope [...]
+Data analysis in live streaming is challenging for the underlying database,
but it is also where the key competitiveness of Apache Doris comes to play.
First of all, Apache Doris can handle most data processing workloads, so
platform builders don't have to worry about putting many components together
and consequential maintenance issues. Secondly, it has a lot of
query-accelerating features, including but not limited to indexes. After
tackling the speed issues, the [Apache Doris develope [...]
diff --git
a/blog/empowering-cyber-security-by-enabling-seven-times-faster-log-analysis.md
b/blog/empowering-cyber-security-by-enabling-seven-times-faster-log-analysis.md
index 84771de01998..9bef5487386a 100644
---
a/blog/empowering-cyber-security-by-enabling-seven-times-faster-log-analysis.md
+++
b/blog/empowering-cyber-security-by-enabling-seven-times-faster-log-analysis.md
@@ -140,4 +140,4 @@ Apart from cluster management, Doris Manager provides a
visualized WebUI for log
-After a month-long trial run, they officially replaced their old LSAS with the
Apache Doris-based system for production, and achieved great results as they
expected. Now, they ingest their 100s of billions of new logs every day via the
[Routine
Load](https://doris.apache.org/docs/dev/data-operate/import/import-way/routine-load-manual/)
method at a speed 3 times as fast as before. Among the 7-time overall query
performance increase, they benefit from a speedup of over 20 times in full-tex
[...]
+After a month-long trial run, they officially replaced their old LSAS with the
Apache Doris-based system for production, and achieved great results as they
expected. Now, they ingest their 100s of billions of new logs every day via the
[Routine
Load](https://doris.apache.org/docs/dev/data-operate/import/import-way/routine-load-manual/)
method at a speed 3 times as fast as before. Among the 7-time overall query
performance increase, they benefit from a speedup of over 20 times in full-tex
[...]
diff --git
a/blog/from-elasticsearch-to-apache-doris-upgrading-an-observability-platform.md
b/blog/from-elasticsearch-to-apache-doris-upgrading-an-observability-platform.md
index ed24282dc3ac..92b4e2ae304b 100644
---
a/blog/from-elasticsearch-to-apache-doris-upgrading-an-observability-platform.md
+++
b/blog/from-elasticsearch-to-apache-doris-upgrading-an-observability-platform.md
@@ -161,8 +161,8 @@ Currently, the Variant type requires extra type assertion,
we plan to automate t
## Conclusion
-GuanceDB's transition from Elasticsearch to Apache Doris showcases a big
stride in improving data processing speed and reducing costs. For these
purposes, Apache Doris has optimized itself in the two major aspects of data
processing: data integration and data analysis. It has expanded its schemaless
support to flexibly accommodate more data types, introduced features like
inverted index and tiered storage to enable faster and more cost-effective
queries. Evolution is an ongoing process. [...]
+GuanceDB's transition from Elasticsearch to Apache Doris showcases a big
stride in improving data processing speed and reducing costs. For these
purposes, Apache Doris has optimized itself in the two major aspects of data
processing: data integration and data analysis. It has expanded its schemaless
support to flexibly accommodate more data types, introduced features like
inverted index and tiered storage to enable faster and more cost-effective
queries. Evolution is an ongoing process. [...]
Check Apache Doris GitHub [repo](https://github.com/apache/doris)
-Find Apache Doris makers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog)
+Find Apache Doris makers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
diff --git
a/blog/how-big-data-is-saving-lives-in-real-time-iov-data-analytics-helps-prevent-accidents.md
b/blog/how-big-data-is-saving-lives-in-real-time-iov-data-analytics-helps-prevent-accidents.md
index 409fca832b31..b4740c54cf70 100644
---
a/blog/how-big-data-is-saving-lives-in-real-time-iov-data-analytics-helps-prevent-accidents.md
+++
b/blog/how-big-data-is-saving-lives-in-real-time-iov-data-analytics-helps-prevent-accidents.md
@@ -109,5 +109,5 @@ Building a data platform to suit your use case is not easy,
I hope this post hel
Apache Doris [GitHub repo](https://github.com/apache/doris)
-Find Apache Doris makers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog)
+Find Apache Doris makers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
diff --git
a/blog/introduction-to-apache-doris-a-next-generation-real-time-data-warehouse.md
b/blog/introduction-to-apache-doris-a-next-generation-real-time-data-warehouse.md
index db39a2bb8d8e..77367e9ced98 100644
---
a/blog/introduction-to-apache-doris-a-next-generation-real-time-data-warehouse.md
+++
b/blog/introduction-to-apache-doris-a-next-generation-real-time-data-warehouse.md
@@ -170,4 +170,4 @@ Roughly speaking, for a data asset consisting of 80% cold
data, tiered storage w
## The Apache Doris Community
-This is an overview of Apache Doris, an open-source real-time data warehouse.
It is actively evolving with an agile release schedule, and the
[community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog)
embraces any questions, ideas, and feedback.
+This is an overview of Apache Doris, an open-source real-time data warehouse.
It is actively evolving with an agile release schedule, and the
[community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
embraces any questions, ideas, and feedback.
diff --git
a/blog/inverted-index-accelerates-text-searches-by-40-time-apache-doris.md
b/blog/inverted-index-accelerates-text-searches-by-40-time-apache-doris.md
index 448acab71335..88923951b179 100644
--- a/blog/inverted-index-accelerates-text-searches-by-40-time-apache-doris.md
+++ b/blog/inverted-index-accelerates-text-searches-by-40-time-apache-doris.md
@@ -507,4 +507,4 @@ Inverted index has been available in Apache Doris for
almost a year and stood th
- **Self-defined tokenization**: provides a user-defined tokenizer to fit in
different use cases.
- **More data types**: Users will be able to create inverted index for complex
data types including Array and Map.
-If you encounter any issues while trying it out in Apache Doris or would like
to know more details, join our
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog)
community and talk to us!
\ No newline at end of file
+If you encounter any issues while trying it out in Apache Doris or would like
to know more details, join our
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
community and talk to us!
\ No newline at end of file
diff --git a/blog/log-analysis-elasticsearch-vs-apache-doris.md
b/blog/log-analysis-elasticsearch-vs-apache-doris.md
index 8bf2e2bee358..02f338a45950 100644
--- a/blog/log-analysis-elasticsearch-vs-apache-doris.md
+++ b/blog/log-analysis-elasticsearch-vs-apache-doris.md
@@ -350,4 +350,4 @@ SELECT * FROM log_table WHERE request MATCH_ALL 'image faq'
ORDER BY ts DESC LIM
If you are looking for an efficient log analytic solution, Apache Doris is
friendly to anyone equipped with SQL knowledge; if you find friction with the
ELK stack, try Apache Doris provides better schema-free support, enables faster
data writing and queries, and brings much less storage burden.
-But we won't stop here. We are going to provide more features to facilitate
log analysis. We plan to add more complicated data types to inverted index, and
support BKD index to make Apache Doris a fit for geo data analysis. We also
plan to expand capabilities in semi-structured data analysis, such as working
on the complex data types (Array, Map, Struct, JSON) and high-performance
string matching algorithm. And we welcome any [user feedback and development
advice](https://t.co/ZxJuNJHXb2).
+But we won't stop here. We are going to provide more features to facilitate
log analysis. We plan to add more complicated data types to inverted index, and
support BKD index to make Apache Doris a fit for geo data analysis. We also
plan to expand capabilities in semi-structured data analysis, such as working
on the complex data types (Array, Map, Struct, JSON) and high-performance
string matching algorithm. And we welcome any [user feedback and development
advice](https://join.slack.com/ [...]
diff --git a/blog/migrating-from-clickhouse-to-apache-doris-what-happened.md
b/blog/migrating-from-clickhouse-to-apache-doris-what-happened.md
index 44c7af977d39..266370d12d91 100644
--- a/blog/migrating-from-clickhouse-to-apache-doris-what-happened.md
+++ b/blog/migrating-from-clickhouse-to-apache-doris-what-happened.md
@@ -159,4 +159,4 @@ In terms of CPU and memory consumption, Apache Doris
maintained stable cluster l
## Future Directions
-As the migration goes on, the user works closely with the [Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog),
and their feedback has contributed to the making of [Apache Doris
2.0.0](https://doris.apache.org/docs/dev/releasenotes/release-2.0.0/). We will
continue assisting them in their migration from Kylin and Druid to Doris, and
we look forward to see their Doris-based unified data platform come into being.
+As the migration goes on, the user works closely with the [Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ),
and their feedback has contributed to the making of [Apache Doris
2.0.0](https://doris.apache.org/docs/dev/releasenotes/release-2.0.0/). We will
continue assisting them in their migration from Kylin and Druid to Doris, and
we look forward to see their Doris-based unified data platform come into being.
diff --git a/blog/release-note-2.0.0.md b/blog/release-note-2.0.0.md
index f703d7c6d624..0a47cd54934a 100644
--- a/blog/release-note-2.0.0.md
+++ b/blog/release-note-2.0.0.md
@@ -235,5 +235,5 @@ This feature allows for higher availability of data,
read/write workload separat
To make Apache Doris 2.0.0 production-ready, we invited hundreds of enterprise
users to engage in the testing and optimized it for better performance,
stability, and usability. In the next phase, we will continue responding to
user needs with agile release planning. We plan to launch 2.0.1 in late August
and 2.0.2 in September, as we keep fixing bugs and adding new features. We also
plan to release an early version of 2.1 in September to bring a few
long-requested capabilities to you. Fo [...]
-If you have any questions or ideas when investigating, testing, and deploying
Apache Doris, please find us on [Slack](https://t.co/ZxJuNJHXb2). Our
developers will be happy to hear them and provide targeted support.
+If you have any questions or ideas when investigating, testing, and deploying
Apache Doris, please find us on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
Our developers will be happy to hear them and provide targeted support.
diff --git a/blog/release-note-2.1.0.md b/blog/release-note-2.1.0.md
index 3272eefe9351..794917905870 100644
--- a/blog/release-note-2.1.0.md
+++ b/blog/release-note-2.1.0.md
@@ -40,7 +40,7 @@ Dear Apache Doris community, we are thrilled to announce the
advent of Apache Do
- **Better workload management**: optimizations of the Workload Group
mechanism for higher performance stability and the display of SQL resource
consumption in the runtime.
-We appreciate the 237 contributors who made nearly 6000 commits in total to
the Apache Doris project, and the nearly 100 enterprise users who provided
valuable feedback. We will keep aiming for the stars with our agile release
planning, and we appreciate your feedback in the [Apache Doris developer and
user
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog).
+We appreciate the 237 contributors who made nearly 6000 commits in total to
the Apache Doris project, and the nearly 100 enterprise users who provided
valuable feedback. We will keep aiming for the stars with our agile release
planning, and we appreciate your feedback in the [Apache Doris developer and
user
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
**Download from GitHub**: https://github.com/apache/doris/releases
diff --git a/blog/variant-in-apache-doris-2.1.md
b/blog/variant-in-apache-doris-2.1.md
index ad93cdc753c0..b7619ad90c42 100644
--- a/blog/variant-in-apache-doris-2.1.md
+++ b/blog/variant-in-apache-doris-2.1.md
@@ -428,4 +428,4 @@ The Doris-based solution also delivers lower CPU usage in
data writing and highe
The Variant data type has stood the test of many users before the official
release of Apache Doris 2.1.0. It is production-available now. In the future,
we plan to realize more lightweight changes for Variant to facilitate data
modeling.
-For more information about Variant and guides on how to build a
semi-structured data analytics solution for your case, come talk to the [Apache
Doris developer
team](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-1t3wfymur-0soNPATWQ~gbU8xutFOLog).
\ No newline at end of file
+For more information about Variant and guides on how to build a
semi-structured data analytics solution for your case, come talk to the [Apache
Doris developer
team](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
\ No newline at end of file
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