Category Archives: Komunitas
Sonnet AWS: Membangun Kustom VPC dengan NAT

… 14 langkah. Referensi soneta sini.

Ini adalah kelas narasi kental 48 dan 49 dari AWS kelas arsitektur Udemy. Narasi jauh lebih cepat untuk sampai ke titik video linear 30 menit akurat dan dapat dibaca di segala arah.


1. Buat VPC, 10.0.0.0/16~~HEAD=dobj.

2. Buat 2 di subnet VPC, karena ketersediaan area “a” dan “b”, 10.0.1.0/24 dan 10.0.2.0/24 masing-masing.

3. Buat gateway web dan menghubungkannya dengan VPC baru. Untuk mengurangi kekacauan – set “Filter VPC” di sudut kiri atas dari panel untuk VPC VPC baru

4 .. Buat VPC baru ke dalam tabel routing, menambah jalan. “0.0.0.0/0 – Internet Gateway” untuk itu

5. Memberi “a” subnet dengan tabel routing baru. Ini akan membuat subnet “ke” publik.

6. Buat grup keamanan untuk membuka SSH masuk, HTTP, HTTPS mana saja.

7. kasus Start “a” subnet “ke” alamat IP publik yang ditugaskan secara otomatis, memilih kelompok keamanan baru.

8. kasus Start “b” di subnet “b” tanpa alamat IP publik secara otomatis ditetapkan ke grup keamanan yang sama.

9 SSH untuk “pada” Misalnya, memastikan bahwa ia memiliki akses ke Internet, seperti “sudo yum install telnet” harus bekerja.

10. “untuk” SSH misalnya, seperti “b”. tidak mengakses internet, seperti “sudo yum install telnet” akan habis.

11 Mulai dari NAT dari citra publik, pilih subnet “a” keadaan IP, dan kelompok keamanan yang sama (untuk demo – adalah sekelompok keamanan samping, prod untuk membuat grup yang terpisah dari lalu lintas antara subnet “b” dari 1,0 .2.0 / 24-NAT).

12 Nonaktifkan kontrol sumber-tujuan seperti NAT (Network Ganti sumber / target cek).

13. Tambahkan tabel routing utama adalah “0.0.0.0/0 – contoh NAT baru” jalan

14 .. Ulangi” sudo yum install telnet “test sebagai contoh” b “-. Harus bekerja sekarang, bahkan jika contoh “b” masih subnet pribadi


Jual minyak shell

Dynamo DB lokal: kurangnya pelatihan untuk Python

Dinamo lokal DB adalah besar alat belajar dan uji
Ini adalah shell JavaScript dengan panduan yang berguna, tapi bicara.
DynamoDBLocal: Download dan jalankan

DynamoDBLocal: JavaScript Shell

Berikut latihan yang sama, diterjemahkan ke Python 2.7.

0 Instal Python 2.7 dan Boto.

1. Mulai dinamo db lokal:
Java Djava.library.path = D: / app / DynamoDB / DynamoDBLocal_lib jar DynamoDBLocal.jar -sharedDb

2. Mulai konsol untuk menampilkan tabel dan perubahan
http: // localhost: 8000 / selimut /

3. Mulai Python

4. Impor Boto
dari boto.dynamodb2.layer1 impor DynamoDBConnection

dari boto.dynamodb2.fields mengimpor HashKey dari meja boto.dynamodb2.table impor

5 terhubung ke Dynamo lokal
conn = DynamoDBConnection (aws_access_key_id = ‘foo’ aws_secret_access_key = ‘bar’ host = 'localhost' port = 8000 is_secure = False)
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; Conn
DynamoDBConnection: localhost

6 ditabulasi daftar
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; conn.list_tables ()
{u'TableNames "[u 'Permainan', u'Image "u'ImageTag" u'x01 "u'z02" u'z_local ']}
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt;

7. Buat tabel dan menggambarkan
z = Table.create ("Z03" model = [HashKey ("XID dimasukkan")] Link = conn);
z.describe ()

8 tabel Menghapus (alias DELETE !!!)

& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; x = tabel ("Z03" Connection conn =) />
{u'Table '{u'TableArn ": u'arn: AWS: DynamoDB: ddblocal: 00000000000
rovisionedThroughput' {u'NumberOfDecreasesToday": 0, u 'WriteCap
0,0} u'TableSizeBytes ": 0, u'TableName": u'z03 "u'TableStatus"
"CreationDateTime": 1,439,230,827.371}}
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; x.delete ()

nyata & amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt;

9. Lepaskan semua tabel
TT = conn.list_tables ()
t TT ['tablenames']:
x = tabel (t = Connection conn);
# x.describe ()
x.delete ()

conn.list_tables ()
{u'TableNames ': []}

9. Buat tabel dengan situasi keseluruhan di
indeks sekunder
dari boto.dynamodb2.fields mengimpor HashKey, RangeKey, KeysOnlyIndex, GlobalAllIndex
dari Boto. Impor meja dynamodb2.table
dari Boto .dynamodb2.types impor NOMOR

image = Table.create ('IMMAGINE'

skema = [HashKey ("id") ]
lulus = {'membaca': 1, 'menulis': 1}
global_indexes = [
GlobalAllIndex (
pihak ImageIndex '= [HashKey ("id" )]
{lulus = "membaca": 1, 'menulis': 1})
]

Connection conn =);

& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; image.describe () {

u'Table '{
u'TableArn ": u'arn: AWS: DynamoDB: ddblocal: 000000000000: desktop / image"
u 'AttributeDefinitions ": [{
u'AttributeName': u'id"
u'AttributeType "
}]
u'GlobalSecondaryIndexes": [{
u'IndexSizeBytes ": 0,
u'IndexName": u'imageIndex "
u'Projection '{
u'ProjectionType": u'ALL "
}
u'ProvisionedThroughput '{
u'WriteCapacityUnits': 1
u'ReadCapacityUnits ": 1}

u'IndexStatus": u'ACTIVE "
u'KeySchema ": [{
u'KeyType": u'HASH "
u'AttributeName ': u'id'
}]
u 'IndexArn ": u'arn: AWS: DynamoDB: ddblocal: 000000000000: desktop / gambar / index / ImageIndex"
u'ItemCount ": 0}
]
u'ProvisionedThroughput' {
u'NumberOfDecreasesToday ": 0,
u'WriteCapacityUnits ': 1
u'LastIncreaseDateTime": 0.0
u'ReadCapacityUnits': 1
u'LastDecreaseDateTime ": 0.0}

u'TableSizeBytes": 0,
u'TableName ": u'image"
u'TableStatus ": u'ACTIVE"
u'KeySchema ": [{
u'KeyType": u'HASH "
u'AttributeName ': u'id'
}]
u'ItemCount": 0
u'CreationDateTime ": 1439232281,427

}}

10 Membuat tabel tanpa
indeks gambar image.delete ()
= Table.create ('IMMAGINE'

skema = [HashKey ("id")]
{lulus = "membaca": 1, 'menulis': 1}
global_indexes = []

Connection conn =);

& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; image.describe () {

u'Table '{
u'TableArn ": u'arn: AWS: DynamoDB: ddblocal: 000000000000: desktop / image"
u 'AttributeDefinitions ": [{
u'AttributeName': u'id"
u'AttributeType '"

u'ProvisionedThroughput U}]' {
u'NumberOfDecreasesToday ': 0,
u'WriteCapacityUnits "1
u'LastIncreaseDateTime': 0.0
u'ReadCapacityUnits ': 1
u'LastDecreaseDateTime" 0.0
}
u'TableSizeBytes ": 0,
u'TableName": u'image "
u'TableStatus": u'ACTIVE "
u'KeySchema": [{
u'KeyType ": u'HASH"
u'AttributeName ":
u'id"}]
u 'ItemCount ": 0,
u'CreationDateTime ": 1439232459.338

}} & amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt;

# perbedaan - ada indeks sekunder global

11 Untuk menyisipkan item pada tabel

waktu impor

time.time #print waktu saat ()

image.put_item (data = {"id": "dynamodb.png", "dateAdded ': time.time () "voteCount '0});

nyata

12 Mendapatkan
elemen
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; x = image.get_item (id = 'dynamodb.png')
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; x

& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; x ['id']
u'dynamodb.png "
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; x ['dateAdded']
desimal ( "1,439,233,446.11100006103515625 ')
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; x ['voteCount']
Decimal ('0')

# convert diperbarui timestamp & amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; dengan datetime
Impor & amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; date.today ()
datetime.date (2015, 8, 10)
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; date.fromtimestamp (x ["dateAdded '])
datetime.date (2015 8, 10)
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt;

13. Menulis Artikel Partai (ukuran maksimum batch 25)

URL = ['android.png', 'appstream.png '' cli.png ',' cloudformation.png '
' cloudfront.png ',' cloudsearch.png ',' cloudtrail.png ',' cloudwatch.png "," pipa .png-data "
'connect.png-langsung "," dotnet.png', 'dynamodb.png', 'ec2.png', 'eclipse.png "," elasticache.png'
'Pohon Kacang karet. png ',' elb.png ',' emr.png ',' glacier.png ',' iam.png ',' ios.png ',' java.png "
'nodejs .png"" opsworks .png ',' php.png ',' powershell.png ',' python.png ',' rds.png ',' redshift.png '
' route53.png ',' 'ruby.png 's3.png', 'ses.png "," SNS .png "," penyimpanan-gateway.png', 'swf.png'
'transcoding.png' 'visual-studio.png' 'vpc.png "
]

LEN (URL)
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; 39

X URL:
dengan image.batch_write () sebagai Group:
batch.put_item (data = {"id": x "dateAdded ': time.time ()" voteCount': 0});
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt;
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; x = image.get_item (id = 'android.png')
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; x

& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; x ['id']
u'android.png "
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt;

14 Pindai seluruh tabel

tt = image.scan ()
t TT:
Tekan tt ['id']

& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; tt = image.scan ()
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; nn = daftar (tt)
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; LEN (nn)

39 & amp; amp; gt; & amp; amp; gt ; & amp; amp; gt;

15 Pindai batas meja / ada batas

#without batas image.scan TT = ( max_page_size = 3)
t TT:
print t ['id'] #returns semua

# Batas

tt = image.scan (limit = 6, max_page_size = 3)
t TT:
print t ['id'] #

6 pengembalian cloudformation.png python.png

cloudsearch.png ec2.png elasticache.png nodejs.png
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt;

16. Buat meja dengan dua indeks

dari boto.dynamodb2.fields mengimpor HashKey, RangeKey, KeysOnlyIndex, GlobalAllIndex
dari Boto .dynamodb2. Impor meja meja
dari Boto. dynamodb2.types NOMOR Impor

dari boto.dynamodb2.fields mengimpor GlobalKeysOnlyIndex dari boto.dynamodb2.fields mengimpor AllIndex
itu Table.create = ("image_tag"
skema = [ HashKey ("tag") RangeKey ("image_id")] melewati
{= "membaca": 1, 'menulis': 1}
global_indexes = [
GlobalKeysOnlyIndex ("image_id_index"
pihak = [HashKey ("image_id") RangeKey ("tag")]
{lulus = "membaca": 1, "tulis": 1}
)
] indeks
= [
AllIndex ("vote_count_index"
pihak = [HashKey ("tag") RangeKey ("vote_count 'data_type = jumlah)]
)
] koneksi
= conn);

& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; it.describe ()
& amp; amp; gt; & amp; amp; gt; it.describe ()
u'Table '{
u'TableArn ": u'arn: AWS: DynamoDB: ddblocal: 000000000000: tabel / image_tag "
u'LocalSecondaryIndexes": [{
u'IndexSizeBytes ": 0,
u'IndexName": u'vote_countindex "
u'Projection" {
u'ProjectionType ": u'ALL"
}
u'IndexArn ": u'arn: AWS: DynamoDB: ddblocal: 000000000000: tabel / image_tag / index / vote_count_index"
u 'KeySchema "[{
u'KeyType": u'HASH "
u'AttributeName": u'tag "
} {

u'KeyType ": u'RANGE"
u'AttributeName ': u'vote_count "
}]
u'ItemCount": 0}
]
u'AttributeDefinitions ": [{
u'AtributeName": u'tag "
u'AttributeType"
} {

u'AttributeName "u 'image_id "
u'AttributeType" U'S'
} {

u'AttributeName ": u'vote_count"
u'AttributeType "u 'N']
u'GlobalSecondaryIndexes ": [{
u'IndexSizeBytes": 0,
u'IndexName ": u'image_id_index"
u'Projection '{
u'ProjectionType ': u'KEYS_ONLY'
}
u'ProvisionedThroughpu '{
u'WriteCapacityUnits "1
u'ReadCapacityUnits": 1}

u'IndexStatus ': u'ACTIVE "
u'KeySchema": [{
u'KeyType ": u'HASH"
u'AttributeName': u'image_id "
} {

u'KeyTpe": u'RANGE "
u'AttributeName": u'tag "
}]
u'IndexArn ": u'arn: AWS: DynamoDB: ddblocal: 000000000000: tabel / image_tag / index / image_id_index"
u'ItemCount ": 0}
]
u 'PrvisionedThroughput' {
u'NumberOfDecreasesToday ": 0,
u'WriteCapacityUnits" 1
u'LastIncreaseDateTime ': 0.0
u'ReadCapacityUnits': 1,
u'LastDecreaseDateTime ': 00}

u'TableSizeBytes ": 0,
u'TableName": u'image_tag "
u'TableStatus': u'ACTIVE"
u'KeySchema ": [{
u'KeyType": u'HASH "
u'AttributeName": u'tag "

{}
u'KeyType ": urange"
u'AttributeName ': u'image_id'
}]
u'ItemCount ": 0,
u 'CreationDateTime": 1439318478.098

}}

17 untuk men-download data dalam tabel
image_tag_index
// program singkat ini akan memuat banyak tabel data sampel ImageTag.
tag // kamus gambar ID untuk menambahkan gambar

{image = 'android.png "[" SDK & amp.; amp; amp; Alat "," Android "]
: ['Layanan Aplikasi," "Amazon AppStream']
['SDK & amp; amp; amp; Tools "" AWS CLI ']
' cloudformation.png ": [" Deployment & amp; amp; amp; Manajemen "," AWS CloudFormation ']
' cloudfront.png '[' Storage & amp; amp; amp; CDN ',' CloudFront ']
' cloudsearch.png ': [' jasa ' "Amazon CloudSearch ']
' cloudtrail.png": ["Deployment & amp; amp; amp; Manajemen "," AWS CloudTrail ']
' cloudwatch.png '[deployment & amp; amp; amp; Manajemen "," Amazon CloudWatch ']
' Data pipeline.png ': [' Analytics ',' AWS data Pipeline ']
' -connect.png langsung '[' untuk menghitung & amp; amp ; amp; Jaringan "," AWS Direct Connect "]
['SDK & amp; amp; Tools", "bersih"]
' dynamodb.png ": [" Database "," Amazon DynamoDB ']
"ec2.png': ['Hitung & amp; amp; amp; Jaringan", "Amazon EC2']
: ['SDK & amp; amp; ; Alat "," Eclipse "]
'elasticache.png": ["database", "Amazon ElastiCache']
" karet beanstalk.png ": [" Deployment & amp; amp; Manajemen ' 'AWS elastis Beanstalk "]
' elb.png ': [' menghitung & amp; amp; amp; Jaringan", "load balancing fleksibel ']
' emr.png ': [' Analytics '" Amazon EMR "]
" glacier.png "['Storage & amp; amp; amp; CDN "," Amazon Glacier ']
' iam.png "[deployment & amp; amp; amp; Management", "AWS IAM"]
'ios.png' ["& amp SDK ; amp; Tools "" IOS "]
: ['SDK & amp; amp ;; Tools", "Java"]
' kinesis.png ': [' Analytics "" Amazon Kinesis ']
' nodejs.png ': [' SDK & amp; amp; amp; Alat "," Node.js ']
' opsworks.png ": [" Deployment & amp; amp; amp; Management "," AWS OpsWorks ']
' php.png ": [" SDK & amp; amp; amp; Alat "," PHP "]
['SDK & amp; amp; amp; Alat "," PowerShell ']
' python.png '[' SDK & amp; amp; amp; alat, "" Python "]
rds.png '": ["database" "Amazon RDS"]
'redshift.png ": [" database "," Amazon pergeseran merah "]
' route53.png ': [' Hitung & amp; amp; amp; Jaringan" "Amazon Route 53"]
'ruby.png' ['SDK & amp; amp; amp; Tools "," Ruby "]
' s3.png" ['Storage & amp; amp; amp; CDN ',' Amazon S3 ']
' ses.png ': [' jasa "," Amazon SES "]
: ['jasa", "Amazon SNS']
'sqs.png': ['jasa', 'Amazon SQS']
'Storage-gateway.png' ['Storage & amp; amp; amp; CDN "," Amazon Storage Gateway ']
' swf.png ': [' jasa "," Amazon SWF "]
: ['Layanan Aplikasi," "Amazon Transcoder fleksibel "]
'visual studio.png' ['SDK & amp; amp; amp; Tools", "Visual Studio"]
' vpc.png ': [' Hitung & amp; amp ; amp; Jaringan "," Amazon VPC ']}

LEN (gambar)
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; 41

i = 0 x gambar:
Tekan X str (gambar [x]), maka
untuk diri mereka sendiri di gambar [x]:
PRINT s

i + = 1 dengan it.batch_write () sebagai Group:
batch.put_item (data = {'image_id': x 'tag' s "vote_count" i });

18. Scan tabel
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; rr = it.scan ()
& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; r rr:
... cetak r ['image_id "], [dari" tag "], [dari" vote_count "]

... vpc.png Amazon VPC 22
rds.png Amazon RDS 6

48 cli.png AWS CLI ios.png iOS 60

8 OpsWorks opsworks.png Data pipeline.png AWS AWS data Pipeline 26
emr.png Amazon ESDM 66

table 19. Query

& amp; amp; gt; & amp; amp; gt ; & amp; amp; gt; rr = it.query_2 ("Database" tag__eq =)
& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; r rr:
. .. print r ['image_id "], [dari" tag "], [dari" vote_count "]

... dynamodb.png database 1

rds.png elasticache.png database database 5 73

31 redshift.png database & amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt;

20 Scanning dengan filter

RR = it.scan (image_id__eq = 'vpc.png ")
tentang rr:
tekan r ['image_id'], r ['tag'], [dari "vote_count ']

... vpc.png Amazon VPC 22
vpc.png perhitungan & amp; amp; amp; Jaringan 21

21 Pertanyaan Indeks
Ini adalah # 19 Flashback: mendapatkan barang tagged "Database "dan vote_index lebih 20.

RR = it.query_2 (indeks = 'vote_count_index' tag__eq = 'Database' vote_count__gt = 5)
untuk RR
tekan r ['image_id "], [dari" tag "], [dari" vote_count']

elasticache.png database 73 & amp; amp; gt; & amp; amp; gt; & amp; amp; gt; rr = it.query_2 (indeks = 'vote_count_index' tag__eq = 'database' vote_count__gt = 5)
& amp; amp; gt; & amp; amp; gt; & amp; Amp; gt; r rr:
... cetak r ['image_id "], [dari" tag "], [dari" vote_count "]

... redshift.png database 31
elasticache.png database 73

22 Query menggunakan indeks, mendapatkan semua tag dalam
gambar RR = en. query_2 (indeks = 'image_id_index' image_id__eq = 'dynamodb.png')
di RR:
print [dari "image_id '] dan [' tag '], [dari" vote_count "]

..

Tidak ada satu dynamodb.png Amazon DynamoDB dynamodb.png database Tidak
& amp; amp; gt; & amp; amp; gt;

23. Buat tabel
variabel
tt = Table.create ("tag" model = [HashKey ("tag")] = Connection conn)

& amp; amp; gt; & amp; amp; gt; & amp; amp; gt; tt.describe () {

u'Table '{u
'TableArn ": u'arn: AWS: DynamoDB: ddblocal: 000000000000: table / tag"
u'AttributeDefinitions ": [{
u'AttributeName': u'tag"
u'AttributeType '"

u'ProvisionedThroughput U}]' {
u'NumberOfDecreasesToday ': 0,
u'WriteCapacityUnits" 5
u' LastIncreaseDateTime ": 0.0
u'ReadCapacityUnits" 5
u'LastDecreaseDateTime "0,0
}
u'TableSizeBytes": 0,
u'TableName ": u'tag "
u'TableStatus": u'ACTIVE "
u'KeySchema": [{
u'KeyType ": u'HASH"
u ' attributeName ": u'tag"
}]
u 'ItemCount ": 0,
u'CreationDateTime": 1439326646,757}


24 untuk memuat data tabel

{tag = "SDK & amp; amp; amp; Instrumen "12,
" layanan aplikasi tercantum dalam "7,
penyebaran & amp; amp; Manajemen": 6
"Storage & amp; amp; amp; CDN": 4,
"Analytics": 3,
"untuk menghitung & amp; amp; amp; Jaringan": 5,
"database": 4,
'Android': 1,
"Amazon AppStream ": 1,
'AWS CLI': 1,
'AWS CloudFormation': 1,
'CloudFront': 1,
" Amazon CloudSearch ": 1
"AWS CloudTrail ': 1,
" AWS data Pipeline ": 1,
" AWS Direct Connect ": 1," bersih "
:
1" Amazon DynamoDB ": 1
"Amazon EC2": 1,
"Eclipse": 1,
"Amazon ElastiCache ': 1,
" fleksibel AWS Beanstalk ": 1
" Fleksibel Load Balancing ': 1,
"Amazon EMR": 1,
"Amazon Glacier': 1,
" AWS IAM ': 1,
' iOS ': 1
'Java': 1,
"Amazon Kinesis ': 1,
" Node.js': 1,
'OpsWorks AWS': 1,
'PHP': 1
"PowerShell": 1,
: 1,
"Amazon RDS": 1,
"Amazon pergeseran merah ': 1,
" Amazon Route 53 ": 1,
Ruby: 1,
" Amazon S3 ": 1,
" Amazon SES ": 1,
" Amazon SNS ": 1
"Amazon SQS ': 1,
" Amazon Storage Gateway': 1,
"Amazon SWF": 1,
"Amazon Elastic Transcoder": 1,
"Visual Studio "1
" Amazon VPC ": 1}

tag X:
Tekan X str (sekarang [x])
dengan dll .batch_write () sebagai Group:
batch.put_item (data = {'tag': x 'IMAGE_COUNT "tag [x]});

& amp; amp; gt; & Amp; Amp; gt; & Amp; Amp; gt; r rr:
... cetak r ['tag'], [dari "IMAGE_COUNT"]

1 ... Amazon VPC Amazon RDS 1
AWS CLI 1 iOS

1 1 OpsWorks AWS AWS data Pipeline 1
Amazon EMR 1

Sherlock Holmes adalah seorang insinyur atau SQL perubahan data seperti yang Anda pikirkan

Berikut ini adalah ide – solusi SQL biasanya mengandalkan pemrograman deduksi -. Induksi

Berdasarkan bukti anekdot, ada perbedaan antara pendekatan praktisi data-driven dan kode berorientasi digunakan. Agaknya alat yang kita gunakan mempengaruhi proses penalaran kita. Tentu saja, “Bila Anda memiliki palu …”

Tampaknya menulis SQL dan pemecahan masalah dengan saat pelaksanaan data dari penalaran deduktif. Desain baru Software dan encode – menggunakan penalaran induktif

Ini adalah alasan mengapa -. Ketika masalah Data -. SDE melompat pohon biner, tetapi Des membuat tabel relasional sebelum

Tentu saja, dikotomi ini datang dengan peringatan biasa.

“Semua generalisasi yang berbahaya, bahkan ini”

Alexandre Dumas