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new 3340cea deploy: cf57935c1428b82edee66a39629ac33600af234e
3340cea is described below
commit 3340cea29eba325d8422dd2cbbd419760231efdd
Author: zabetak <[email protected]>
AuthorDate: Tue Feb 11 09:21:33 2025 +0000
deploy: cf57935c1428b82edee66a39629ac33600af234e
---
docs/latest/158869886/index.html | 2 +-
docs/latest/170266662/index.html | 2 +-
docs/latest/283118454/index.html | 2 +-
docs/latest/50858744/index.html | 4 +-
.../index.html | 4 +-
.../correlation-optimizer_34019487/index.html | 12 ++--
.../index.html | 8 +--
docs/latest/design_27362072/index.html | 2 +-
.../index.html | 2 +-
docs/latest/hcatalog-usinghcat_34013260/index.html | 2 +-
docs/latest/hive-metrics_65872987/index.html | 2 +-
docs/latest/languagemanual-orc_31818911/index.html | 2 +-
docs/latest/llap_62689557/index.html | 2 +-
docs/latest/presentations_27362054/index.html | 80 +++++++++++-----------
.../setting-up-hiveserver2_30758712/index.html | 2 +-
.../index.html | 6 +-
.../webhcat-usingwebhcat_34015492/index.html | 2 +-
17 files changed, 68 insertions(+), 68 deletions(-)
diff --git a/docs/latest/158869886/index.html b/docs/latest/158869886/index.html
index af9016e..b39200a 100644
--- a/docs/latest/158869886/index.html
+++ b/docs/latest/158869886/index.html
@@ -160,7 +160,7 @@ ASF
<h2 id=overview>Overview</h2>
<p>The overall design of the gRPC support in Hive Metastore is illustrated in
Fig.1. On the server side, based on user configuration, the Hive Metastore
Server can listen on a port for Thrift or gRPC request. The lifecycle of a
Thrift request has not been changed. For a gRPC request, the new
<em>HiveMetastoreGrpcServer</em> will translate an incoming gRPC request into a
Thrift request, transparently pass it to <em>HiveMetastoreThriftServer</em>,
and translate the response back into gRPC.</p>
<p>On the client side, a similar design is used to support converting outgoing
requests from Thrift to gRPC. </p>
-<p><img src=attachments/158869886/158869888.png alt></p>
+<p><img src=/attachments/158869886/158869888.png alt></p>
<p>Figure 1. An overview of the new gRPC endpoint of Hive Metastore.
<em>Clarification: The only network I/O that occurs is between the user and
serving processes in</em> <em>HiveMetaStore</em> <em>(gRPC, Thrift, or
both).</em></p>
<p>The implementation details are described in the following sections.</p>
<h2 id=implementation>Implementation</h2>
diff --git a/docs/latest/170266662/index.html b/docs/latest/170266662/index.html
index b07c358..2a9f56a 100644
--- a/docs/latest/170266662/index.html
+++ b/docs/latest/170266662/index.html
@@ -128,7 +128,7 @@ ASF
<li>For the first version we will not support encrypted SAML assertions (since
it would mean we need to exchange the public key of HiveServer2 with IDP) and
will instead rely on the end-to-end TLS encryption for the connections between
client and server. However, the SAML responses generated by IDP MUST be signed
to validate the authenticity of the response.</li>
</ol>
<h4 id=saml-authentication-workflow>SAML authentication workflow</h4>
-<p><img src=attachments/170266662/170266668.png alt></p>
+<p><img src=/attachments/170266662/170266668.png alt></p>
<h4 id=authentication-flow-details>Authentication Flow Details</h4>
<ol>
<li><strong>JDBC Driver</strong>: Receives a connection url from the
user-facing clients (Beeline, Tableau). The connection URL uses http transport
and has auth=browser</li>
diff --git a/docs/latest/283118454/index.html b/docs/latest/283118454/index.html
index f4dc7cb..edba8ec 100644
--- a/docs/latest/283118454/index.html
+++ b/docs/latest/283118454/index.html
@@ -232,7 +232,7 @@ ASF
<li>Releasing the lock.</li>
</ol>
<h1 id=example>Example</h1>
-<p><img
src="attachments/283118454/283118455.png?effects=border-simple,blur-border"
alt></p>
+<p><img
src="/attachments/283118454/283118455.png?effects=border-simple,blur-border"
alt></p>
<p>So to recap, the sequence of events required to apply mutations to a
dataset using the API is:</p>
<ol>
<li>Create a <code>MutatorClient</code> to manage a transaction for the
targeted ACID tables. This set of tables should include any transactional
destinations or sources. Don’t forget to register a
<code>LockFailureListener</code> so that you can handle transaction
failures.</li>
diff --git a/docs/latest/50858744/index.html b/docs/latest/50858744/index.html
index 5752582..366aa40 100644
--- a/docs/latest/50858744/index.html
+++ b/docs/latest/50858744/index.html
@@ -144,7 +144,7 @@ ASF
</ul>
<p>Each processor box shows the triggering condition, either a Hive
configuration property, or the presence of a certain operator in the tree. So,
you can see how to trigger a particular join by following its path through
processors and making sure all configurations are triggered and the given
operator has been created by previous processors. There are further conditions
to do the transform listed on the top, (ie, size of table, etc), that are not
be explained by this document, and ca [...]
<h3 id=figure-1-join-processors-for-hive-on-mapreduce>Figure 1. Join
Processors for Hive on MapReduce</h3>
-<p><img
src="attachments/50858744/51183928.png?effects=border-simple,blur-border"
alt></p>
+<p><img
src="/attachments/50858744/51183928.png?effects=border-simple,blur-border"
alt></p>
<p>The input arrow at top before any Processor is always an operator-plan for
common-join, which is shown as follows. In other words, this is the original
join plan if none of the optimizer processors are activated.</p>
<p><img
src=https://lh5.googleusercontent.com/6XjRKhcU5NqlT2-45wDW9f3lS188yRFFLzTVcPK77RKrrV6P2Box7n_qLxse7tdaH968Pnfg29ErRWzFWgYclNIwNFBus91eqoCGddM4hTmm8R-n2q39k3RtoH_1y7Jm5g
alt></p>
<p>The ‘exit’ arrows of the join paths shown in Figure 1 are the various
optimized join variants. There are of course other exit paths, in which the
plan remains unchanged as a common-join upon falling out of any processor’s
pre-req checks, but they are not shown to simplify the diagram.</p>
@@ -305,7 +305,7 @@ ASF
<li>Hive on Spark’s SMB to MapJoin conversion path is simplified, by directly
converting to MapJoin if eligible.</li>
</ul>
<h3 id=figure-2-join-processors-for-hive-on-spark>Figure 2: Join Processors
for Hive on Spark</h3>
-<p><img
src="attachments/50858744/51183929.png?effects=border-simple,blur-border"
alt></p>
+<p><img
src="/attachments/50858744/51183929.png?effects=border-simple,blur-border"
alt></p>
<p>Again, we first explore some of the interesting processors:</p>
<p> </p>
<ul>
diff --git a/docs/latest/accessserver-design-proposal_31823045/index.html
b/docs/latest/accessserver-design-proposal_31823045/index.html
index e3e87c5..bf425e8 100644
--- a/docs/latest/accessserver-design-proposal_31823045/index.html
+++ b/docs/latest/accessserver-design-proposal_31823045/index.html
@@ -154,11 +154,11 @@ ASF
<p>Before discussing these modifications it is important to first understand
the basic design of HiveServer2.</p>
<h3 id=hiveserver2-design-overview>HiveServer2 Design Overview</h3>
<p>The following diagram is a block-level representation of the major
submodules in HiveServer2 with horizontal boundaries signifying dependencies.
Green modules existed in Hive before the HiveServer2 project commenced, while
blue modules were implemented as part of the HiveServer2 project.</p>
-<p><img src=attachments/31823045/31949154.png alt></p>
+<p><img src=/attachments/31823045/31949154.png alt></p>
<p>The core of HiveServer2 is the HiveSession class. This class provides a
container for user session state and also manages the lifecycle of operations
triggered by the user. In this context an operation is any command exposed
through the CLIService API that can generate a result set. This includes the
ExecuteStatement() operation and metadata operations such as GetTables() and
GetSchemas(). Each of these operations is implemented by a specific Operation
subclass. In order to execute Hi [...]
<h3 id=accessserver-design>AccessServer Design</h3>
<p>The following diagram gives a quick overview of the changes required to
support the Pig runtime engine in AccessServer. For simplicity we have removed
Hive-specific components from the diagram such as the HiveOperation and
HiveSession classes.</p>
-<p><img src=attachments/31823045/31949155.png alt></p>
+<p><img src=/attachments/31823045/31949155.png alt></p>
<p>In the diagram blue denotes existing components in HiveServer2 that do not
require modification. This includes the Thrift interface, JDBC/ODBC drivers,
CLIService, and the Metastore.</p>
<p>Orange denotes existing HiveServer2 components that must be modified. We
need to modify the SessionManager in order to support pluggable session
factories. Note that the CLIService API already allows clients to request a
specific Session type via a set of configuration parameters that are part of
the OpenSession call.</p>
<p>Yellow denotes new components that must be fashioned from scratch: the
PigSession class and the set of Pig Operation classes. The following
implementation details relevant to these classes are worth noting:</p>
diff --git a/docs/latest/correlation-optimizer_34019487/index.html
b/docs/latest/correlation-optimizer_34019487/index.html
index b2e59b2..bd91088 100644
--- a/docs/latest/correlation-optimizer_34019487/index.html
+++ b/docs/latest/correlation-optimizer_34019487/index.html
@@ -133,10 +133,10 @@ WHERE t1.value > tmp1.avg
GROUP BY /*AGG2*/ tmp1.key;
</code></pre><p>The original operator tree generated by Hive is shown
below.</p>
-<p><img src=attachments/34019487/34177453.png alt></p>
+<p><img src=/attachments/34019487/34177453.png alt></p>
<p><strong>Figure 1: The original operator tree of Example 1 generated by
Hive</strong></p>
<p>This plan uses three MapReduce jobs to evaluate this query. However,
<code>AGG1</code>, <code>JOIN1</code>, and <code>AGG2</code> all require the
column <code>key</code> to be the partitioning column for shuffling the data.
Thus, we do not need to shuffle the data in the same way three times. We only
need to shuffle the data once, and thus a single MapReduce job is needed. The
optimized operator tree is shown below.</p>
-<p><img src=attachments/34019487/34177454.png alt></p>
+<p><img src=/attachments/34019487/34177454.png alt></p>
<p><strong>Figure 2: The optimized operator tree of Example 1</strong></p>
<p>Since the input table of <code>AGG1</code> and the left table of
<code>JOIN1</code> are both <code>t1</code>, when we use a single MapReduce job
to evaluate this query, Hive only needs to scan <code>t1</code> once. While, in
the original plan, <code>t1</code> is used in two MapReduce jobs, and thus it
is scanned twice.</p>
<h3 id=22-example-2>2.2 Example 2</h3>
@@ -150,10 +150,10 @@ WHERE t2.value > tmp1.avg
GROUP BY /*AGG2*/ t1.key;
</code></pre><p>The original operator tree generated by Hive is shown
below.</p>
-<p><img src=attachments/34019487/34177455.png alt></p>
+<p><img src=/attachments/34019487/34177455.png alt></p>
<p><strong>Figure 3: The original operator tree of Example 2 generated by
Hive</strong></p>
<p>This example is similar to Example 1. The optimized operator tree only
needs a single MapReduce job, which is shown below.</p>
-<p><img src=attachments/34019487/34177456.png alt></p>
+<p><img src=/attachments/34019487/34177456.png alt></p>
<p><strong>Figure 4: The optimized operator tree of Example 2</strong></p>
<h3 id=23-example-3>2.3 Example 3</h3>
<pre tabindex=0><code>SELECT count(distinct ws1.ws_order_number) as
order_count,
@@ -182,10 +182,10 @@ WHERE d.d_date >= '2001-05-01' and
s.web_company_name = 'pri';
</code></pre><p>The original operator tree generated by Hive is shown
below.</p>
-<p><img src=attachments/34019487/34177457.png alt></p>
+<p><img src=/attachments/34019487/34177457.png alt></p>
<p><strong>Figure 5: The original operator tree of Example 3 generated by
Hive</strong></p>
<p>In this complex query, we will first have several MapJoins
(<code>MJ1</code>, <code>MJ2</code>, and <code>MJ3</code>) which can be
evaluated in the same Map phase. Since <code>JOIN1</code>, <code>JOIN2</code>,
<code>JOIN3</code>, and <code>JOIN4</code> use the same column as the join key,
we can use a single MapReduce job to evaluate all operators before
<code>AGG1</code>. The second MapReduce job will generate the final results.
The optimized operator tree is shown below.</p>
-<p><img src=attachments/34019487/34177458.png alt></p>
+<p><img src=/attachments/34019487/34177458.png alt></p>
<p><strong>Figure 6: The optimized operator tree of Example 3</strong></p>
<h2 id=3-intra-query-correlations>3. Intra-query Correlations</h2>
<p>In Hive, a submitted SQL query needs to be evaluated in a distributed
system. When evaluating a query, data may need to shuffled sometimes. Based on
the nature of different data operations, operators in Hive can be divided to
two categories.</p>
diff --git a/docs/latest/cost-based-optimization-in-hive_42566775/index.html
b/docs/latest/cost-based-optimization-in-hive_42566775/index.html
index fd570b4..b25225a 100644
--- a/docs/latest/cost-based-optimization-in-hive_42566775/index.html
+++ b/docs/latest/cost-based-optimization-in-hive_42566775/index.html
@@ -186,7 +186,7 @@ ASF
<li>Lucid DB</li>
<li>Mondrian/Pentaho</li>
</ul>
-<p><img src=attachments/42566775/51183721.jpg alt></p>
+<p><img src=/attachments/42566775/51183721.jpg alt></p>
<p>Calcite currently has over fifty cost based optimization rules. Some of the
prominent cost based optimization rules are listed below:</p>
<ul>
<li>Push Join through Union</li>
@@ -297,7 +297,7 @@ ASF
<h1 id=4-implementation-details>4. Implementation details</h1>
<p>CBO will be introduced in to Hive in three different phases. Following
provides high-level overview of these phases: </p>
<h2 id=phase-1>Phase 1</h2>
-<p> <img src=attachments/42566775/51183717.jpg alt></p>
+<p> <img src=/attachments/42566775/51183717.jpg alt></p>
<p>Statistics:</p>
<ul>
<li>Table Cardinality</li>
@@ -350,7 +350,7 @@ ASF
</ul>
<p> </p>
<h2 id=phase-2>Phase 2</h2>
-<p><img src=attachments/42566775/51183718.jpg alt></p>
+<p><img src=/attachments/42566775/51183718.jpg alt></p>
<p>Statistics:</p>
<ul>
<li>Histograms</li>
@@ -363,7 +363,7 @@ ASF
<li>Take advantage of additional optimizations in Calcite. The actual rules to
use is TBD.</li>
</ul>
<h2 id=phase-3>Phase 3</h2>
-<p><img src=attachments/42566775/51183719.jpg alt></p>
+<p><img src=/attachments/42566775/51183719.jpg alt></p>
<h2 id=configuration>Configuration</h2>
<p>The configuration parameter <a href=#hive-cbo-enable>hive.cbo.enable</a>
determines whether cost-based optimization is enabled or not.</p>
<h2 id=proposed-cost-model>Proposed Cost Model</h2>
diff --git a/docs/latest/design_27362072/index.html
b/docs/latest/design_27362072/index.html
index 84989aa..f7193ab 100644
--- a/docs/latest/design_27362072/index.html
+++ b/docs/latest/design_27362072/index.html
@@ -133,7 +133,7 @@ ASF
<li><a href=#hive-apis>Hive APIs</a></li>
</ul>
<p>Figure 1<br>
-<img src=attachments/27362072/47743299.png alt></p>
+<img src=/attachments/27362072/47743299.png alt></p>
<h2 id=hive-architecture>Hive Architecture</h2>
<p>Figure 1 shows the major components of Hive and its interactions with
Hadoop. As shown in that figure, the main components of Hive are:</p>
<ul>
diff --git a/docs/latest/hcatalog-streaming-mutation-api_61337025/index.html
b/docs/latest/hcatalog-streaming-mutation-api_61337025/index.html
index eec84f6..3457f38 100644
--- a/docs/latest/hcatalog-streaming-mutation-api_61337025/index.html
+++ b/docs/latest/hcatalog-streaming-mutation-api_61337025/index.html
@@ -232,7 +232,7 @@ ASF
<li>Releasing the lock.</li>
</ol>
<h1 id=example>Example</h1>
-<p><img
src="attachments/61337025/61337024.png?effects=border-simple,blur-border"
alt></p>
+<p><img
src="/attachments/61337025/61337024.png?effects=border-simple,blur-border"
alt></p>
<p>So to recap, the sequence of events required to apply mutations to a
dataset using the API is:</p>
<ol>
<li>Create a <code>MutatorClient</code> to manage a transaction for the
targeted ACID tables. This set of tables should include any transactional
destinations or sources. Don’t forget to register a
<code>LockFailureListener</code> so that you can handle transaction
failures.</li>
diff --git a/docs/latest/hcatalog-usinghcat_34013260/index.html
b/docs/latest/hcatalog-usinghcat_34013260/index.html
index 13cb2bb..9d63635 100644
--- a/docs/latest/hcatalog-usinghcat_34013260/index.html
+++ b/docs/latest/hcatalog-usinghcat_34013260/index.html
@@ -143,7 +143,7 @@ Hive version 0.11.0 is the first release that includes
HCatalog.</p>
<h2 id=overview>Overview</h2>
<p>HCatalog is a table and storage management layer for Hadoop that enables
users with different data processing tools — Pig, MapReduce — to more easily
read and write data on the grid. HCatalog’s table abstraction presents users
with a relational view of data in the Hadoop distributed file system (HDFS) and
ensures that users need not worry about where or in what format their data is
stored — RCFile format, text files, SequenceFiles, or ORC files.</p>
<p>HCatalog supports reading and writing files in any format for which a SerDe
(serializer-deserializer) can be written. By default, HCatalog supports RCFile,
CSV, JSON, and SequenceFile, and ORC file formats. To use a custom format, you
must provide the InputFormat, OutputFormat, and SerDe.</p>
-<p><img src=attachments/34013260/34177026.jpg alt></p>
+<p><img src=/attachments/34013260/34177026.jpg alt></p>
<h2 id=hcatalog-architecture>HCatalog Architecture</h2>
<p>HCatalog is built on top of the Hive metastore and incorporates
Hive’s DDL. HCatalog provides read and write interfaces for Pig and
MapReduce and uses Hive’s command line interface for issuing data
definition and metadata exploration commands.</p>
<h3 id=interfaces>Interfaces</h3>
diff --git a/docs/latest/hive-metrics_65872987/index.html
b/docs/latest/hive-metrics_65872987/index.html
index eb32950..17b814c 100644
--- a/docs/latest/hive-metrics_65872987/index.html
+++ b/docs/latest/hive-metrics_65872987/index.html
@@ -117,7 +117,7 @@ ASF
<h1 id=apache-hive--hive-metrics>Apache Hive : Hive Metrics</h1>
<p>The metrics that Hive collects can be viewed in the <a
href=#hiveserver2-web-ui>HiveServer2 Web UI</a> by using the “Metrics
Dump” tab.</p>
<p>The metrics dump will display any metric available over JMX encoded in
JSON: </p>
-<p><img src=attachments/65872987/65874398.png alt></p>
+<p><img src=/attachments/65872987/65874398.png alt></p>
<p>Alternatively the metrics can be written directly into HDFS, a JSON file on
the local file system where the HS2 instance is running or to the console by
enabling the corresponding metric reporters. By default only the JMX and the
JSON file reporter are enabled.</p>
<p>These metrics include:</p>
<ul>
diff --git a/docs/latest/languagemanual-orc_31818911/index.html
b/docs/latest/languagemanual-orc_31818911/index.html
index c09d908..16dbdfb 100644
--- a/docs/latest/languagemanual-orc_31818911/index.html
+++ b/docs/latest/languagemanual-orc_31818911/index.html
@@ -169,7 +169,7 @@ ASF
<p>The default stripe size is 250 MB. Large stripe sizes enable large,
efficient reads from HDFS.</p>
<p>The file footer contains a list of stripes in the file, the number of rows
per stripe, and each column’s data type. It also contains column-level
aggregates count, min, max, and sum.</p>
<p>This diagram illustrates the ORC file structure:</p>
-<p><img src=attachments/31818911/31948932.png alt></p>
+<p><img src=/attachments/31818911/31948932.png alt></p>
<h3 id=stripe-structure>Stripe Structure</h3>
<p>As shown in the diagram, each stripe in an ORC file holds index data, row
data, and a stripe footer.</p>
<p>The <strong>stripe footer</strong> contains a directory of stream
locations. <strong>Row data</strong> is used in table scans.</p>
diff --git a/docs/latest/llap_62689557/index.html
b/docs/latest/llap_62689557/index.html
index 14fc1be..e70a401 100644
--- a/docs/latest/llap_62689557/index.html
+++ b/docs/latest/llap_62689557/index.html
@@ -145,7 +145,7 @@ Functionality such as caching, pre-fetching, some query
processing and access co
<p>Similar to the DataNode, LLAP daemons can be used by other applications as
well, especially if a relational view on the data is preferred over
file-centric processing. The daemon is also open through optional APIs (e.g.,
InputFormat) that can be leveraged by other data processing frameworks as a
building block.</p>
<p>Last, but not least, fine-grained column-level access control – a key
requirement for mainstream adoption of Hive – fits nicely into this model.</p>
<p>The diagram below shows an example execution with LLAP. Tez AM orchestrates
overall execution. The initial stage of the query is pushed into LLAP. In the
reduce stage, large shuffles are performed in separate containers. Multiple
queries and applications can access LLAP concurrently.</p>
-<p><img src=attachments/62689557/65871225.png alt></p>
+<p><img src=/attachments/62689557/65871225.png alt></p>
<h2 id=persistent-daemon>Persistent Daemon</h2>
<p>To facilitate caching and JIT optimization, and to eliminate most of the
startup costs, a daemon runs on the worker nodes on the cluster. The daemon
handles I/O, caching, and query fragment execution.</p>
<ul>
diff --git a/docs/latest/presentations_27362054/index.html
b/docs/latest/presentations_27362054/index.html
index 46183b3..798475f 100644
--- a/docs/latest/presentations_27362054/index.html
+++ b/docs/latest/presentations_27362054/index.html
@@ -136,43 +136,43 @@ ASF
<h1 id=hive-meetups>Hive Meetups</h1>
<h2 id=january-2016-hive-user-group-meetup>January 2016 Hive User Group
Meetup</h2>
<ul>
-<li><a
href=/attachments/27362054/61337098-pptx>attachments/27362054/61337098-pptx</a></li>
-<li><a
href=/attachments/27362054/61337312-ppsx>attachments/27362054/61337312-ppsx</a></li>
-<li><a
href=/attachments/27362054/61337398-ppsx>attachments/27362054/61337398-ppsx</a></li>
+<li><a
href=/attachments/27362054/61337098.pptx>attachments/27362054/61337098-pptx</a></li>
+<li><a
href=/attachments/27362054/61337312.ppsx>attachments/27362054/61337312-ppsx</a></li>
+<li><a
href=/attachments/27362054/61337398.ppsx>attachments/27362054/61337398-ppsx</a></li>
<li><a
href="https://cwiki.apache.org/confluence/download/attachments/27362054/Hive%20User%20Group%20Meeting%20Jan%202016.pdf?api=v2";>Hive
on Spark: now and future - Xuefu Zhang</a></li>
</ul>
<h2 id=november-2015-hive-contributor-meetup>November 2015 Hive Contributor
Meetup</h2>
<ul>
-<li><a
href=/attachments/27362054/61329032-pptx>attachments/27362054/61329032-pptx</a></li>
-<li><a
href=/attachments/27362054/61329033-pptx>attachments/27362054/61329033-pptx</a></li>
-<li><a
href=/attachments/27362054/61329034-pptx>attachments/27362054/61329034-pptx</a></li>
-<li><a
href=/attachments/27362054/61329036-pptx>attachments/27362054/61329036-pptx</a></li>
-<li><a
href=/attachments/27362054/61329038-pptx>attachments/27362054/61329038-pptx</a></li>
+<li><a
href=/attachments/27362054/61329032.pptx>attachments/27362054/61329032-pptx</a></li>
+<li><a
href=/attachments/27362054/61329033.pptx>attachments/27362054/61329033-pptx</a></li>
+<li><a
href=/attachments/27362054/61329034.pptx>attachments/27362054/61329034-pptx</a></li>
+<li><a
href=/attachments/27362054/61329036.pptx>attachments/27362054/61329036-pptx</a></li>
+<li><a
href=/attachments/27362054/61329038.pptx>attachments/27362054/61329038-pptx</a></li>
<li><a
href=/attachments/27362054/61329039.pdf>attachments/27362054/61329039.pdf</a></li>
-<li><a
href=/attachments/27362054/61329040-pptx>attachments/27362054/61329040-pptx</a></li>
-<li><a
href=/attachments/27362054/61329311-ppsx>attachments/27362054/61329311-ppsx</a></li>
+<li><a
href=/attachments/27362054/61329040.pptx>attachments/27362054/61329040-pptx</a></li>
+<li><a
href=/attachments/27362054/61329311.ppsx>attachments/27362054/61329311-ppsx</a></li>
</ul>
<h2 id=april-2015-hive-contributor-meetup-presentations>April 2015 Hive
Contributor Meetup Presentations</h2>
<ul>
<li><a
href=https://github.com/julianhyde/share/blob/master/slides/hive-sqlline-twins-2015.pdf>SQLLine
- The tale of the twins that everyone loved too much – Julian Hyde</a></li>
<li><a
href=/attachments/27362054/56131586.pdf>attachments/27362054/56131586.pdf</a></li>
-<li><a
href=/attachments/27362054/55476525-pptx>attachments/27362054/55476525-pptx</a></li>
-<li><a
href=/attachments/27362054/55476526-pptx>attachments/27362054/55476526-pptx</a></li>
+<li><a
href=/attachments/27362054/55476525.pptx>attachments/27362054/55476525-pptx</a></li>
+<li><a
href=/attachments/27362054/55476526.pptx>attachments/27362054/55476526-pptx</a></li>
</ul>
<h2 id=february-2015-hive-user-meetup-presentation>February 2015 Hive User
Meetup Presentation</h2>
<ul>
-<li><a
href=/attachments/27362054/52036008-pptx>attachments/27362054/52036008-pptx</a>
(Szehon Ho)</li>
+<li><a
href=/attachments/27362054/52036008.pptx>attachments/27362054/52036008-pptx</a>
(Szehon Ho)</li>
<li><a
href=/attachments/27362054/52036063.pdf>attachments/27362054/52036063.pdf</a>
(Ryan Desmond)</li>
</ul>
<h2 id=november-2013-hive-contributors-meetup-presentations>November 2013 Hive
Contributors Meetup Presentations</h2>
<ul>
-<li><a
href=/attachments/27362054/35193152-pptx>attachments/27362054/35193152-pptx</a>
(Edward Capriolo)</li>
-<li><a
href=/attachments/27362054/35193150-pptx>attachments/27362054/35193150-pptx</a>
(Gunther Hagleitner)</li>
-<li><a
href=/attachments/27362054/35193153-pptx>attachments/27362054/35193153-pptx</a>
(Thejas Nair)</li>
-<li><a
href=/attachments/27362054/35193154-pptx>attachments/27362054/35193154-pptx</a>
(Owen O’Malley)</li>
+<li><a
href=/attachments/27362054/35193152.pptx>attachments/27362054/35193152-pptx</a>
(Edward Capriolo)</li>
+<li><a
href=/attachments/27362054/35193150.pptx>attachments/27362054/35193150-pptx</a>
(Gunther Hagleitner)</li>
+<li><a
href=/attachments/27362054/35193153.pptx>attachments/27362054/35193153-pptx</a>
(Thejas Nair)</li>
+<li><a
href=/attachments/27362054/35193154.pptx>attachments/27362054/35193154-pptx</a>
(Owen O’Malley)</li>
<li><a
href=http://www.slideshare.net/brocknoland/hive-contributors-meetup-apache-sentry>Apache
Sentry</a> (Brock Noland)</li>
-<li><a
href=/attachments/27362054/35193151-pptx>attachments/27362054/35193151-pptx</a>
(John Pullokkaran)</li>
-<li><a
href=/attachments/27362054/35193149-pptx>attachments/27362054/35193149-pptx</a>
(Ashutosh Chauhan)</li>
+<li><a
href=/attachments/27362054/35193151.pptx>attachments/27362054/35193151-pptx</a>
(John Pullokkaran)</li>
+<li><a
href=/attachments/27362054/35193149.pptx>attachments/27362054/35193149-pptx</a>
(Ashutosh Chauhan)</li>
</ul>
<h2 id=june-2013-hadoop-summit-hive-meetup-presentations>June 2013 Hadoop
Summit Hive Meetup Presentations</h2>
<ul>
@@ -274,55 +274,55 @@ ASF
<p><img src=images/icons/bullet_blue.gif alt>
<a
href=/attachments/27362054/30966880.pdf>attachments/27362054/30966880.pdf</a>
(application/pdf)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/35193149-pptx>attachments/27362054/35193149-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/35193149.pptx>attachments/27362054/35193149-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/35193150-pptx>attachments/27362054/35193150-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/35193150.pptx>attachments/27362054/35193150-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/35193151-pptx>attachments/27362054/35193151-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/35193151.pptx>attachments/27362054/35193151-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/35193152-pptx>attachments/27362054/35193152-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/35193152.pptx>attachments/27362054/35193152-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/35193153-pptx>attachments/27362054/35193153-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/35193153.pptx>attachments/27362054/35193153-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/35193154-pptx>attachments/27362054/35193154-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/35193154.pptx>attachments/27362054/35193154-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/52036008-pptx>attachments/27362054/52036008-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/52036008.pptx>attachments/27362054/52036008-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
<a
href=/attachments/27362054/52036063.pdf>attachments/27362054/52036063.pdf</a>
(application/pdf)</p>
<p><img src=images/icons/bullet_blue.gif alt>
<a
href=/attachments/27362054/55476524-key>attachments/27362054/55476524-key</a>
(application/x-iwork-keynote-sffkey)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/55476525-pptx>attachments/27362054/55476525-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/55476525.pptx>attachments/27362054/55476525-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/55476526-pptx>attachments/27362054/55476526-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/55476526.pptx>attachments/27362054/55476526-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
<a
href=/attachments/27362054/56131586.pdf>attachments/27362054/56131586.pdf</a>
(application/download)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/61329032-pptx>attachments/27362054/61329032-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/61329032.pptx>attachments/27362054/61329032-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/61329033-pptx>attachments/27362054/61329033-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/61329033.pptx>attachments/27362054/61329033-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
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href=/attachments/27362054/61329034-pptx>attachments/27362054/61329034-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/61329034.pptx>attachments/27362054/61329034-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/61329036-pptx>attachments/27362054/61329036-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
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(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
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href=/attachments/27362054/61329038-pptx>attachments/27362054/61329038-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/61329038.pptx>attachments/27362054/61329038-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
<a
href=/attachments/27362054/61329039.pdf>attachments/27362054/61329039.pdf</a>
(application/pdf)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/61329040-pptx>attachments/27362054/61329040-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
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(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
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href=/attachments/27362054/61329311-ppsx>attachments/27362054/61329311-ppsx</a>
(application/vnd.openxmlformats-officedocument.presentationml.slideshow)</p>
+<a
href=/attachments/27362054/61329311.ppsx>attachments/27362054/61329311-ppsx</a>
(application/vnd.openxmlformats-officedocument.presentationml.slideshow)</p>
<p><img src=images/icons/bullet_blue.gif alt>
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href=/attachments/27362054/61337098-pptx>attachments/27362054/61337098-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
href=/attachments/27362054/61337098.pptx>attachments/27362054/61337098-pptx</a>
(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
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href=/attachments/27362054/61337312-ppsx>attachments/27362054/61337312-ppsx</a>
(application/vnd.openxmlformats-officedocument.presentationml.slideshow)</p>
+<a
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(application/vnd.openxmlformats-officedocument.presentationml.slideshow)</p>
<p><img src=images/icons/bullet_blue.gif alt>
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(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
+<a
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(application/vnd.openxmlformats-officedocument.presentationml.presentation)</p>
<p><img src=images/icons/bullet_blue.gif alt>
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href=/attachments/27362054/61337399-ppsx>attachments/27362054/61337399-ppsx</a>
(application/vnd.openxmlformats-officedocument.presentationml.slideshow)</p>
+<a
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(application/vnd.openxmlformats-officedocument.presentationml.slideshow)</p>
<p><img src=images/icons/bullet_blue.gif alt>
-<a
href=/attachments/27362054/61337398-ppsx>attachments/27362054/61337398-ppsx</a>
(application/vnd.openxmlformats-officedocument.presentationml.slideshow)</p>
+<a
href=/attachments/27362054/61337398.ppsx>attachments/27362054/61337398-ppsx</a>
(application/vnd.openxmlformats-officedocument.presentationml.slideshow)</p>
<p><img src=images/icons/bullet_blue.gif alt>
<a
href=/attachments/27362054/61337443.pdf>attachments/27362054/61337443.pdf</a>
(application/pdf)</p>
</div>
diff --git a/docs/latest/setting-up-hiveserver2_30758712/index.html
b/docs/latest/setting-up-hiveserver2_30758712/index.html
index 082da6f..5c24791 100644
--- a/docs/latest/setting-up-hiveserver2_30758712/index.html
+++ b/docs/latest/setting-up-hiveserver2_30758712/index.html
@@ -349,7 +349,7 @@ usage: hiveserver2
<li><a href=#logs>Logs</a>can be viewed by using the “Local logs”
tab.</li>
</ul>
<p>The interface is currently under development with <a
href=https://issues.apache.org/jira/browse/HIVE-12338>HIVE-12338</a>.</p>
-<p><img src=attachments/30758712/61336258.png alt></p>
+<p><img src=/attachments/30758712/61336258.png alt></p>
<h2 id=python-client-driver>Python Client Driver</h2>
<p>A Python client driver for HiveServer2 is available at <a
href=https://github.com/BradRuderman/pyhs2>https://github.com/BradRuderman/pyhs2</a>
(thanks, Brad). It includes all the required packages such as SASL and Thrift
wrappers.</p>
<p>The driver has been certified for use with Python 2.6 and newer.</p>
diff --git a/docs/latest/synchronized-metastore-cache_110692851/index.html
b/docs/latest/synchronized-metastore-cache_110692851/index.html
index a347db8..95c16aa 100644
--- a/docs/latest/synchronized-metastore-cache_110692851/index.html
+++ b/docs/latest/synchronized-metastore-cache_110692851/index.html
@@ -119,10 +119,10 @@ ASF
<p>This work is to solve the consistency problem if we use HMS HA with
metadata cache. Note it does not aim to address any existing consistency issues
already exist in non-cached HMS. For example, it won’t fix the transaction
semantic between metadata and data. If the problem exists today in non-cached
HMS, it stays a problem after this work.</p>
<p>The problem we try to solve here is the cache consistency issue. We already
build a HMS cache to cache the metadata. If we have multiple HMS in the
cluster, the cache is not synchronized. That is, if metastore 1 changed a
table/partition, metastore 2 won’t see the change immediately. There’s a
background thread keep polling from the notification log and update changed
entries, so the cache is eventually consistent. In this work, we want to make
the cache full consistent. The idea is a [...]
<p>.</p>
-<p><img src=attachments/110692851/110692853.png alt></p>
+<p><img src=/attachments/110692851/110692853.png alt></p>
<h1 id=data-structure-change>Data structure change</h1>
<p>The only data structure change is adding ValidWriteIdList into
SharedCache.TableWrapper, which represents the transaction state of the cached
table.</p>
-<p><img src=attachments/110692851/110692854.png alt></p>
+<p><img src=/attachments/110692851/110692854.png alt></p>
<p>Note there is no db table structure change, and we don’t store extra
information in db. We don’t update TBLS.WRITE_ID field as we will use db as the
fact of truth. We assume db always carry the latest copy and every time we
fetch from db, we will tag it with the transaction state of the query.</p>
<h1 id=how-it-works>How It Works</h1>
<h2 id=read>Read</h2>
@@ -155,7 +155,7 @@ ASF
<li>The cache update thread will further read commit event from notification
log, mark writeid 12 as committed, the tag of cached table entry changed to
[12:7,8]</li>
<li>The next read from HMS 2 will serve from cache</li>
</ol>
-<p><img src=attachments/110692851/110692855.png alt></p>
+<p><img src=/attachments/110692851/110692855.png alt></p>
<h2 id=bootstrap>Bootstrap</h2>
<p>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 ValidWriteI [...]
<h2 id=maintain-writeid>Maintain WriteId</h2>
diff --git a/docs/latest/webhcat-usingwebhcat_34015492/index.html
b/docs/latest/webhcat-usingwebhcat_34015492/index.html
index 4dfcbdc..5959a3f 100644
--- a/docs/latest/webhcat-usingwebhcat_34015492/index.html
+++ b/docs/latest/webhcat-usingwebhcat_34015492/index.html
@@ -144,7 +144,7 @@ Hive version 0.11.0 is the first release that includes
HCatalog and its REST API
<h2 id=introduction-to-webhcat>Introduction to WebHCat</h2>
<p>This document describes the HCatalog REST API, <em>WebHCat</em>, which was
previously called <em>Templeton</em>. If you are looking for a Hive GUI instead
of an API, see <a
href=https://hive.apache.org/docs/latest/hivewebinterface_27362110/>Hive Web
Interface</a> (removed in release 2.2.0).</p>
<p>As shown in the figure below, developers make HTTP requests to access <a
href=http://hadoop.apache.org/>Hadoop</a> <a
href=http://hadoop.apache.org/docs/stable/mapred_tutorial.html>MapReduce</a>
(or <a
href=http://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html>YARN</a>),
<a href=http://pig.apache.org/>Pig</a>, <a
href=http://hive.apache.org/>Hive</a>, and <a href=#hcatalog-ddl>HCatalog
DDL</a> from within applications. Data and code used by this API are maintain
[...]
-<p><img src=attachments/34015492/34177184.jpg alt></p>
+<p><img src=/attachments/34015492/34177184.jpg alt></p>
<p>WebHCat or Templeton?</p>
<p>For backward compatibility, the original name Templeton is still used for
WebHCat in some contexts. See <a href=##project-name>#Project Name</a>
below.</p>
<h2 id=url-format>URL Format</h2>
